Tuğba Özge Onur | Image Reconstruction | Best Researcher Award

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Assoc. Prof. Dr. Tuğba Özge Onur | Image Reconstruction | Best Researcher Award

Associate Professor | Zonguldak Bülent Ecevit University | Turkey

Assoc. Prof. Dr. Tuğba Özge Onur is a distinguished researcher specializing in signal processing, image reconstruction, and optimization. She earned her Ph.D. in electrical and electronics engineering from a leading university, where she developed a strong foundation in computational imaging and algorithm design. Her professional experience includes leading research projects, coordinating international collaborations, and mentoring students in both academic and applied research settings. Her research interests span computer vision, optimization techniques, and advanced signal processing methods, with a focus on developing innovative solutions for real-world challenges. She possesses a diverse set of research skills, including algorithm development, data analysis, experimental design, and implementation of complex computational models. She is actively engaged in the scientific community through professional memberships and collaborative initiatives. Her work has been widely recognized and published in reputed journals and conferences, demonstrating both the depth and impact of her contributions. Her commitment to advancing knowledge, mentoring emerging researchers, and participating in collaborative projects underscores her influence in the field. 98 Citations, 23 Documents, 6 h-index.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Onur, T. Ö. (2022). Improved image denoising using wavelet edge detection based on Otsu’s thresholding. Acta Polytechnica Hungarica, 19(2), 79–92.

  2. Onur, Y. A., İmrak, C. E., & Onur, T. Ö. (2017). Investigation on bending over sheave fatigue life determination of rotation resistant steel wire rope. Experimental Techniques, 41(5), 475–482.

  3. Narin, D., & Onur, T. Ö. (2022). The effect of hyperparameters on the classification of lung cancer images using deep learning methods. Erzincan University Journal of Science and Technology, 15(1), 258–268.

  4. Kaya, G. U., & Onur, T. Ö. (2022). Genetic algorithm based image reconstruction applying the digital holography process with the Discrete Orthonormal Stockwell Transform technique for diagnosis of COVID-19. Computers in Biology and Medicine, 148, 105934.

  5. Onur, T. (2021). An application of filtered back projection method for computed tomography images. International Review of Applied Sciences and Engineering, 12(2), 194–200.

Fatma Zahra Sayadi | Deep Learning | Best Innovation Award

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Prof. Fatma Zahra Sayadi | Deep Learning | Best Innovation Award

Associate Professor | University of Sousse | Tunisia

Fatma Elzahra Sayadi is a highly accomplished researcher and academic specializing in electronics and microelectronics, with current research focused on video surveillance systems, real-time processing, and signal compression. She earned her PhD in electronics for real-time systems from the University of Bretagne Sud in collaboration with the University of Monastir and has also completed her engineering and master’s studies in electrical and electronic systems. She has extensive professional experience as a maître de conférences and previously as a maître assistante and assistant technologist, teaching courses in microprocessors, multiprocessors, programming, circuit testing, and industrial electronics. Her research interests include signal processing, parallel architectures, microelectronics, real-time systems, and communication networks. She has actively participated in national and international research projects and collaborations with institutions in France, Italy, Germany, and Morocco. Her work has been published in over 37 journal articles, 40 conference papers, and six book chapters, and she has supervised several doctoral and master’s theses. She has been recognized with awards such as the first prize at the Women in Research Forum at the University of Sharjah and contributes to professional communities as a reviewer, evaluator, and organizer of academic events. She is skilled in research methodologies, signal and data analysis, electronic system design, and digital education innovation. Her academic contributions have been cited by 395 documents, with 69 documents contributing to her citations, and she has an h-index of 13.

Profile: Google Scholar | Scopus | ORCID 

Featured Publications

  1. Basly, H., Ouarda, W., Sayadi, F. E., Ouni, B., & Alimi, A. M. (2020). CNN-SVM learning approach based human activity recognition. In International Conference on Image and Signal Processing (pp. 271–281). 77 citations.

  2. Bouaafia, S., Khemiri, R., Sayadi, F. E., & Atri, M. (2020). Fast CU partition-based machine learning approach for reducing HEVC complexity. Journal of Real-Time Image Processing, 17(1), 185–196. 53 citations.

  3. Haggui, O., Tadonki, C., Lacassagne, L., Sayadi, F., & Ouni, B. (2018). Harris corner detection on a NUMA manycore. Future Generation Computer Systems, 88, 442–452. 48 citations.

  4. Basly, H., Ouarda, W., Sayadi, F. E., Ouni, B., & Alimi, A. M. (2022). DTR-HAR: Deep temporal residual representation for human activity recognition. The Visual Computer, 38(3), 993–1013. 40 citations.

  5. Bouaafia, S., Khemiri, R., Messaoud, S., Ben Ahmed, O., & Sayadi, F. E. (2022). Deep learning-based video quality enhancement for the new versatile video coding. Neural Computing and Applications, 34(17), 14135–14149. 35 citations.

Naga Nithin Katta | Image Processing | Best Researcher Award

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Mr. Naga Nithin Katta | Image Processing | Best Researcher Award

Employee at Oppo | India

Naga Nithin Katta is a highly motivated computer science and engineering professional with a strong focus on innovation, research, and problem-solving. His expertise spans artificial intelligence, machine learning, computer vision, and full stack development, areas in which he has applied his skills to impactful projects. He has gained industrial exposure as a software engineer at OPPO, where he contributed to projects involving video stream analysis, automation of testing frameworks, and mobile AI deployment. Alongside his industry experience, he has been an active mentor in data structures and algorithms, helping students strengthen their problem-solving abilities. His leadership has been recognized through international competitions, including selection among the Top 100 teams globally in the Google Solution Challenge and multiple hackathon victories. With a balance of technical knowledge, practical implementation, and a passion for community contribution, he is steadily building a strong foundation as an emerging researcher with promising leadership potential.

Professional Profile

Scopus Profile

Education

Naga Nithin Katta is pursuing a Bachelor of Technology in Computer Science and Engineering at VNR Vignana Jyothi Institute of Engineering and Technology, where he has been developing a strong academic background in computing principles, software engineering, and applied technologies. Prior to this, he successfully completed a diploma in computer science from the Government Institute of Electronics, which provided him with a solid technical base in programming, database management, and system design. His educational journey has been complemented by active participation in research-oriented projects, hackathons, and collaborative learning platforms that encouraged innovation and problem-solving. He has consistently demonstrated academic excellence by integrating classroom knowledge with practical applications, which is evident in his project work and international recognition through competitive platforms. This strong educational foundation has equipped him with both theoretical and applied perspectives, allowing him to bridge the gap between academia and industry while nurturing his passion for research and development.

Professional Experience

Naga Nithin Katta has gained valuable professional experience as a software engineer at OPPO, where he contributed to significant projects aimed at improving efficiency and automation in mobile technologies. His work involved developing web applications using Vue.js and MySQL for managing project statuses, implementing video stream analysis through OpenCV and Python, and deploying AI models on mobile devices using ONNX and Beeware. He played a key role in creating a UI automation system powered by large language models, reducing manual testing efforts and enhancing accuracy. Additionally, he contributed to building a network operator testing automation tool, streamlining processes and reducing workforce requirements. Alongside his industry work, he served as a student mentor at SmartInterviews, guiding learners in data structures and algorithms and preparing them for technical challenges. This blend of industrial expertise and teaching experience reflects his versatility, ability to collaborate across teams, and passion for applying research in practical contexts.

Research Interest

Naga Nithin Katta’s research interests lie primarily in the fields of artificial intelligence, computer vision, natural language processing, and software engineering, with a particular focus on developing innovative solutions that bridge academic research and real-world applications. He has worked on projects such as sign language converters that integrate computer vision with generative AI and cloud technologies, reflecting his interest in human-computer interaction and accessibility-focused applications. His engagement with large language models and UI automation tools demonstrates his curiosity in advancing human-machine interaction and automated testing frameworks. Additionally, his focus on video stream analysis and frame detection highlights his inclination towards multimedia research and visual computing. He is also keen on exploring areas such as deep learning optimization, mobile AI deployment, and cloud-integrated intelligent systems. His vision is to contribute to impactful solutions that enhance everyday technologies while simultaneously pursuing scholarly outputs that advance scientific knowledge.

Research Skill

Naga Nithin Katta has developed strong research skills that enable him to design, implement, and evaluate innovative solutions across different domains of computer science. He is proficient in programming languages such as C, C++, Python, and Java, and demonstrates advanced knowledge in full stack development with tools like ReactJs, Vue.js, and MySQL. His expertise in AI and machine learning is reflected in projects involving computer vision, natural language processing, and model deployment on mobile devices. He has practical experience in research-driven software development, having implemented algorithms for video frame detection, gesture recognition, and UI automation powered by large language models. His familiarity with tools like OpenCV, ONNX, Flask, and cloud-based APIs allows him to conduct applied research efficiently. He also possesses strong problem-solving abilities, demonstrated by his role as a mentor in data structures and algorithms. His skills in bridging theoretical concepts with industrial applications showcase his potential as a future research leader.

Publications Top Notes

Title: Optical Motion Detection Language Generator: A Survey

Year: 2025

Conclusion

Naga Nithin Katta is a deserving candidate for the Best Researcher Award as he has consistently demonstrated innovation, technical expertise, and leadership in both academic and industrial settings. His impactful projects, including advancements in computer vision, automation, and AI-driven solutions, showcase contributions that address real-world challenges and benefit society. With proven recognition in global competitions, mentorship roles, and industry research experience, he has already made meaningful strides as an emerging researcher. With a continued focus on publishing in reputed venues and building stronger international collaborations, he holds significant potential to become a future leader in the research and technology community.

Puja Gupta | Computer Vision | Excellence in Research

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Dr. Puja Gupta | Computer Vision | Excellence in Research

Asst Professor at Shri G.S. Institute of Technology & Science | India

Dr. Puja Gupta is a dedicated researcher and academic with expertise in artificial intelligence, machine learning, IoT, and smart computing technologies. She has contributed significantly to the field through her high-quality publications in reputed journals, patents, and innovative product development. Her work has addressed real-world challenges in healthcare, security, and sustainable technologies, bridging the gap between research and practical applications. With a strong academic foundation, she has successfully guided students in research and projects, fostering innovation and academic growth. She has been actively involved in international collaborations, research projects, and academic leadership roles, contributing to the advancement of her field. She is also a committed member of professional organizations, demonstrating her engagement in the broader research community. Her impactful contributions, leadership potential, and dedication to continuous professional development make her a valuable asset to both academia and society.

Professional Profile 

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Puja Gupta holds a strong academic background in computer science and engineering, culminating in a doctoral degree specializing in artificial intelligence and smart systems. Her Ph.D. research focused on the integration of machine learning techniques and IoT frameworks to design intelligent solutions that address complex societal problems. Prior to her doctoral studies, she earned her master’s and bachelor’s degrees in computer science, gaining a solid foundation in algorithms, data structures, and system design. Throughout her academic journey, she demonstrated exceptional commitment to learning, consistently achieving top ranks and recognition for her research contributions. Her advanced education has equipped her with in-depth knowledge of computational intelligence, optimization techniques, and applied research methodologies, enabling her to contribute effectively to both theoretical advancements and practical applications in the field. Her academic background continues to support her innovative research and teaching excellence in the areas of AI, IoT, and emerging technologies.

Professional Experience

Dr. Puja Gupta has extensive professional experience in both academic and research domains, with a focus on artificial intelligence, IoT, and smart computing solutions. She has worked as a faculty member at prestigious institutions, where she has taught and mentored students at undergraduate and postgraduate levels, guiding them in research projects and fostering innovation. Alongside teaching, she has been actively involved in funded research projects, many of which involved international collaborations and multidisciplinary teams. She has successfully published her findings in reputed journals and conferences indexed in IEEE and Scopus, and her work has also resulted in patents and prototypes with practical applications. Beyond academia, she has contributed to the research community by serving as a reviewer, participating in editorial activities, and organizing academic events. Her leadership roles in academic programs and community-driven initiatives further highlight her commitment to advancing knowledge and supporting the development of future researchers.

Research Interest

Dr. Puja Gupta’s research interests revolve around artificial intelligence, machine learning, IoT, big data analytics, and smart system design. She is particularly focused on developing intelligent solutions that address pressing societal challenges in areas such as healthcare, security, and sustainability. Her work often integrates computational intelligence with real-world applications, such as predictive healthcare models, smart monitoring systems, and secure communication frameworks for IoT devices. She is also keen on advancing research in explainable AI and optimization algorithms to ensure reliability and transparency in machine learning systems. Another area of interest is the development of resource-efficient AI models for deployment in edge and cloud environments. Her multidisciplinary approach allows her to collaborate across domains, leveraging data-driven techniques to innovate practical solutions. By combining theoretical knowledge with applied research, she aims to contribute to technological advancements that enhance the quality of life and create sustainable, impactful outcomes for society.

Award and Honor

Dr. Puja Gupta has been recognized with numerous awards and honors that highlight her academic excellence, research contributions, and leadership in the field of computer science and engineering. Her achievements include recognition for publishing impactful research in reputed journals, presenting at leading international conferences, and securing patents that demonstrate the practical value of her work. She has also been honored for her contributions to student mentoring and academic program development, reflecting her dedication to nurturing young talent. Several of her awards acknowledge her innovative approaches in AI and IoT research, particularly for developing solutions with direct societal impact. In addition, she has received appreciation for her involvement in community-driven initiatives and leadership in professional organizations. These honors not only recognize her past accomplishments but also serve as a testament to her commitment, perseverance, and ability to inspire others in the academic and research communities.

Research Skill

Dr. Puja Gupta possesses advanced research skills in artificial intelligence, machine learning, IoT systems, and computational modeling, enabling her to conduct impactful and interdisciplinary research. She is proficient in applying data analysis techniques, optimization algorithms, and predictive modeling to design intelligent solutions for real-world applications. Her expertise includes working with various programming languages, simulation tools, and research frameworks that support scalable and innovative problem-solving. She has developed strong skills in experimental design, result validation, and research dissemination through high-quality publications and conference presentations. Beyond technical expertise, she excels in collaborative research, often working with international teams and multidisciplinary groups to drive innovation. She is also skilled in project management, proposal writing, and securing research funding, which have been instrumental in the successful execution of her projects. Her research skills, combined with her commitment to continuous learning, position her as a versatile and resourceful academic and researcher in her field.

Publications Top Notes

Title: Impact of knowledge management practices on innovative capacity: A study of telecommunication sector
Authors: J Jyoti, P Gupta, S Kotwal
Year: 2011
Citation: 56

Title: A Novel Algorithm for Mask Detection and Recognizing Actions of Human
Authors: P Gupta, V Sharma, S Varma
Year: 2022
Citation: 48

Title: Transcriptional mechanisms underlying sensitization of peripheral sensory neurons by granulocyte-/granulocyte-macrophage colony stimulating factors
Authors: KK Bali, V Venkataramani, VP Satagopam, P Gupta, R Schneider, …
Year: 2013
Citation: 42

Title: Minimally invasive plate osteosynthesis (MIPO) for proximal and distal fractures of the tibia: a biological approach
Authors: P Gupta, A Tiwari, A Thora, JK Gandhi, VP Jog
Year: 2016
Citation: 41

Title: SUMOylation of enzymes and ion channels in sensory neurons protects against metabolic dysfunction, neuropathy, and sensory loss in diabetes
Authors: N Agarwal, FJ Taberner, DR Rojas, M Moroni, D Omberbasic, C Njoo, …
Year: 2020
Citation: 39

Title: An introduction of soft computing approach over hard computing
Authors: P Gupta, N Kulkarni
Year: 2013
Citation: 31

Title: People detection and counting using YOLOv3 and SSD models
Authors: P Gupta, V Sharma, S Varma
Year: 2021
Citation: 30

Title: Challenges in the adaptation of IoT technology
Authors: Neha, P Gupta, MA Alam
Year: 2021
Citation: 20

Title: Role of fine needle aspiration cytology in preoperative diagnosis of ameloblastoma
Authors: S Bisht, SA Kotwal, P Gupta, R Dawar
Year: 2009
Citation: 13

Title: Let the Blind See: An AIIoT based device for real-time object recognition with the voice conversion
Authors: P Gupta, M Shukla, N Arya, U Singh, K Mishra
Year: 2022
Citation: 9

Title: The impact of artificial intelligence on renewable energy systems
Authors: P Gupta, S Kumar, YB Singh, P Singh, SK Sharma, NK Rathore
Year: 2022
Citation: 8

Title: Simultaneous feature selection and clustering of micro-array and RNA-sequence gene expression data using multiobjective optimization
Authors: AK Alok, P Gupta, S Saha, V Sharma
Year: 2020
Citation: 8

Title: Activity detection and counting people using mask-RCNN with bidirectional ConvLSTM
Authors: P Gupta, U Singh, M Shukla
Year: 2022
Citation: 7

Title: Study of cloud providers (azure, amazon, and oracle) according to service availability and price
Authors: A Rajput, P Gupta, P Ghodeshwar, S Varma, KK Sharma, U Singh
Year: 2023
Citation: 6

Title: Machine learning approaches for IoT-data classification
Authors: O Farooq, P Gupta
Year: 2020
Citation: 5

Title: Evaluation of AI system’s voice recognition performance in social conversation
Authors: SK Barnwal, P Gupta
Year: 2022
Citation: 4

Title: Analysis of CNN Model with Traditional Approach and Cloud AI based Approach
Authors: U Kushwaha, P Gupta, S Airen, M Kuliha
Year: 2022
Citation: 4

Title: Analysis of crowd features based on deep learning
Authors: P Gupta, V Sharma, S Varma
Year: 2022
Citation: 4

Title: Acknowledgment of patient in sense behaviors using bidirectional ConvLSTM
Authors: U Singh, P Gupta, M Shukla, V Sharma, S Varma, SK Sharma
Year: 2023
Citation: 3

Title: Study on the NB-IoT based smart medical system
Authors: P Gupta, AK Pandey
Year: 2023
Citation: 3

Conclusion

Dr. Puja Gupta is highly deserving of the Best Researcher Award for her significant contributions to advancing research in artificial intelligence, IoT, and smart technologies, as well as her role in mentoring students and fostering innovation. Her impactful work, including patents, high-quality publications, and practical product development, has addressed societal challenges in healthcare, security, and sustainability. With her strong academic background, leadership in academic and community initiatives, and commitment to continuous growth, she holds great potential to further excel in future research, expand global collaborations, and take on greater leadership roles in the academic and research community.

Prof Dr. Amar Hassan Khamis | Machine Learning for Computer Vision | Best Researcher Award

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Prof Dr. Amar Hassan Khamis | Machine Learning for Computer Vision | Best Researcher Award

Prof Dr. Amar Hassan Khamis | Mohammed Bin Rashid University of Medicine and Health Sciences | United Arab Emirates

Dr. Amar Hassan Khamis holds a Ph.D. in Biostatistics & Genetic Epidemiology (2003) from the University of Méditerranée AIX Marseille and the University of Gazira under a sandwich program. He also earned a DEA in Biostatistics from the University of Paris XI (1994) and a certificate in Medical and Biological Studies with a focus on epidemiology and biostatistics (1991).

Professional Profiles

Google Scholar

Scopus

Orcid

🎓Academic  Qualifications 

Dr. Khamis boasts a robust academic background, having completed a PhD in Biostatistics & Genetic Epidemiology through a sandwich program between University of Méditerranée AIX Marseille, France, and University of Gazira, Sudan in 2003. His other qualifications include a DEA in Biostatistics from the University Paris XI, France, and a Certificate in Medical and Biological Studies with a focus on Epidemiology and Biostatistics. Additionally, he holds a B.Sc. in Statistics & Computer Science from the University of Khartoum, Sudan.

🏢Professional Career Highlights  

Dr. Amar Hassan Khamis is a distinguished Professor of Biostatistics, currently serving at the Hamdan Bin Mohammed College of Dental Medicine, part of the Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU) in Dubai since January 17, 2018. Renowned for his expertise, he has also contributed as an Adjunct Professor at Ajman University, teaching Biostatistics and Research Methods for postgraduate dentistry programs. Over his extensive career, Dr. Khamis has held key academic roles at esteemed institutions like the University of Dammam, KSA, University of Khartoum, Sudan, and the Ahfad University for Women, Sudan, demonstrating unwavering commitment to the field of Biostatistics and health sciences.

📚🧑‍🏫Teaching and Mentorship 

Dr. Khamis has a prolific teaching portfolio, having taught a variety of courses across undergraduate and postgraduate levels, including Mathematics, Biostatistics, Research Methodology, Clinical Trials, and Epidemiology. His professional workshops on Meta-Analysis, Advanced Biostatistics, and Respondent Driven Sampling are highly acclaimed. Moreover, he has supervised numerous higher diploma, MSc, and PhD theses, playing a pivotal role in advancing biostatistical research and application.

🌐🤝Global Collaboration and Leadership 

Dr. Khamis has played significant roles in global health initiatives, including consulting for WHO EMRO and conducting missions across the Eastern Mediterranean region. As a member of the Board of Research Committee of ALBASAR International Foundation and other international scientific associations, he has facilitated cross-border collaborations. His contributions to achieving the Millennium Development Goals (MDGs) in Africa highlight his dedication to improving public health outcomes.

🛠️💻Training and Skill Development 

An expert in statistical computing, Dr. Khamis is proficient in tools like SPSS, Stata, R-language, and Comprehensive Meta-Analysis (CMA). He has attended several advanced training programs worldwide, including courses on Meta-Analysis, Health Management, and Population Surveys at renowned institutions such as Johns Hopkins Bloomberg School of Public Health and Oxford University.

🏅🌟Recognition and Honors 

Dr. Khamis has been acknowledged as a pioneer in biostatistics, playing a transformative role in his academic and professional engagements. He has served as an external examiner for universities across Africa and the Middle East and as a member of research ethics committees in Sudan, Saudi Arabia, and the UAE.

Publications Top Noted 📝

Three-dimensional computed tomography analysis of airway volume in growing class II patients treated with Frankel II appliance

Authors: Ahmed, M.J.; Diar-Bakirly, S.; Deirs, N.; Hassan, A.; Ghoneima, A.

Journal: Head and Face Medicine

Year: 2024

Comparative Assessment of Pharyngeal Airway Dimensions in Skeletal Class I, II, and III Emirati Subjects: A Cone Beam Computed Tomography Study

Authors: AlAskar, S.; Jamal, M.; Khamis, A.H.; Ghoneima, A.

Journal: Dentistry Journal

Year: 2024

High-fidelity simulation versus case-based tutorial sessions for teaching pharmacology: Convergent mixed methods research investigating undergraduate medical students’ performance and perception

Authors: Kaddoura, R.; Faraji, H.; Otaki, F.; Khamis, A.H.; Jan, R.K.

Journal: PLoS ONE

Year: 2024

Enamel demineralization around orthodontic brackets bonded with new bioactive composite (in-vitro study)

Authors: Ali, N.A.M.; Nissan, L.M.K.; Al-Taai, N.; Khamis, A.H.

Journal: Journal of Baghdad College of Dentistry

Year: 2024

Do Hall Technique Crowns Affect Intra-arch Dimensions? A Split-mouth Quasi-experimental Non-randomized Feasibility Pilot Study

Authors: Alramzi, B.; Alhalabi, M.; Kowash, M.; Ghoneima, A.; Hussein, I.

Journal: International Journal of Clinical Pediatric Dentistry

Year: 2024

Assoc Prof Dr. Peixian Zhuang | Image Processing | Best Researcher Award

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Assoc Prof Dr. Peixian Zhuang | Image Processing | Best Researcher Award

Peixian Zhuang at University of Science and Technology Beijing, China

👨‍🎓 Profiles

Scopus

Google Scholar

Publications

CVANet: Cascaded visual attention network for single image super-resolution

  • Authors: Weidong Zhang, Wenyi Zhao, Jia Li, Peixian Zhuang, Haihan Sun, Yibo Xu, Chongyi Li
  • Journal: Neural Networks
  • Year: 2024

Underwater image enhancement via piecewise color correction and dual prior optimized contrast enhancement

  • Authors: Weidong Zhang, Songlin Jin, Peixian Zhuang, Zheng Liang, Chongyi Li
  • Journal: IEEE Signal Processing Letters
  • Year: 2023

Non-uniform illumination underwater image restoration via illumination channel sparsity prior

  • Authors: Guojia Hou, Nan Li, Peixian Zhuang, Kunqian Li, Haihan Sun, Chongyi Li
  • Journal: IEEE Transactions on Circuits and Systems for Video Technology
  • Year: 2023

Gacnet: Generate adversarial-driven cross-aware network for hyperspectral wheat variety identification

  • Authors: Weidong Zhang, Zexu Li, Guohou Li, Peixian Zhuang, Guojia Hou, Qiang Zhang, Chongyi Li
  • Journal: IEEE Transactions on Geoscience and Remote Sensing
  • Year: 2023

Underwater image enhancement via minimal color loss and locally adaptive contrast enhancement

  • Authors: Weidong Zhang, Peixian Zhuang, Hai-Han Sun, Guohou Li, Sam Kwong, Chongyi Li
  • Journal: IEEE Transactions on Image Processing
  • Year: 2022

Prof. Zhi Gao | Image Processing | Best Researcher Award

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Prof. Zhi Gao, Image Processing, Best Researcher Award

Zhi Gao at Wuhan University, China

Professional Profile

Summary:

Zhi Gao is a highly accomplished Professor and Doctoral Supervisor at the School of Remote Sensing and Information Engineering, Wuhan University. He holds prestigious positions as the National Young Talent Program and Distinguished Professor of Hubei Province, China. With a solid background in engineering and extensive experience in academia and research, he has built strong collaborative networks with renowned universities and institutions worldwide.

👩‍🎓Education:

Zhi Gao received his Bachelor of Engineering (B.Eng.) and Doctor of Philosophy (Ph.D.) degrees from Wuhan University, China, in 2002 and 2007, respectively. His educational background provides him with a strong foundation in his field.

🧬 Work Experience:

Zhi Gao’s professional journey reflects a wealth of experience in both academia and industry. Highlights of his career include:

  • Research Fellow (A) and Project Manager at the Interactive and Digital Media Institute, National University of Singapore (NUS), Singapore, since 2008.
  • Research Scientist (A) at the Temasek Laboratories, NUS, contributing significantly to research endeavors.
  • Building strong collaborative relationships with prestigious institutions globally, including the Temasek Laboratory, National University of Singapore, Carnegie Mellon University Robotics Institute, Robert Gordon University, The Chinese University of Hong Kong, Beijing Normal University, and Beijing Institute of Technology.

Research Interests:

  • Computer Vision
  • Machine Learning
  • Remote Sensing
  • UAV-based Surveillance Research and Applications

Publications Top Noted:

Paper Title: Exploring the relationship between land use change patterns and variation in environmental factors within urban agglomeration
  • Authors: Xiao, R., Yin, H., Liu, R., Liu, L., Jia, T.
  • Journal: Sustainable Cities and Society
  • Volume: 108
  • Pages: 105447
  • Year: 2024
  • Citations: 0
Paper Title: Tracking by Detection: Robust Indoor RGB-D Odometry Leveraging Key Local Manhattan World
  • Authors: Zhou, Z., Gao, Z., Xu, J.
  • Journal: IEEE Robotics and Automation Letters
  • Volume: 9
  • Issue: 6
  • Pages: 4990–4997
  • Year: 2024
Paper Title: How Challenging is a Challenge? CEMS: a Challenge Evaluation Module for SLAM Visual Perception
  • Authors: Zhao, X., Gao, Z., Li, H., Fang, H., Chen, B.M.
  • Journal: Journal of Intelligent and Robotic Systems: Theory and Applications
  • Volume: 110
  • Issue: 1
  • Pages: 42
  • Year: 2024
  • Citations: 0
Paper Title: TJ-FlyingFish: An Unmanned Morphable Aerial–Aquatic Vehicle System
  • Authors: Liu, X., Dou, M., Yan, R., Chen, J., Chen, B.M.
  • Journal: Unmanned Systems
  • Volume: 12
  • Issue: 2
  • Pages: 409–428
  • Year: 2024
  • Citations: 1
Paper Title: WaterFormer: A Global-Local Transformer for Underwater Image Enhancement With Environment Adaptor
  • Authors: Wen, J., Cui, J., Yang, G., Dou, L., Chen, B.M.
  • Journal: IEEE Robotics and Automation Magazine
  • Volume: 31
  • Issue: 1
  • Pages: 29–40
  • Year: 2024
  • Citations: 1

 

Image Processing and Enhancement

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Introduction Image Processing and Enhancement:

Image Processing and Enhancement is a pivotal domain within the realm of computer vision and digital imaging. This field is dedicated to the development of algorithms and techniques that improve the quality, clarity, and interpretability of digital images. Whether it's enhancing the visibility of medical scans, restoring historical photographs, or improving image quality in satellite imagery, this research area has widespread applications across various industries.

Subtopics in Image Processing and Enhancement:

  1. Image Denoising and Restoration: Research in this subfield focuses on developing algorithms to remove noise and artifacts from images, making them clearer and more suitable for analysis or presentation.
  2. Image Super-Resolution: This subtopic explores methods to enhance the resolution of images, enabling the generation of high-resolution images from lower-resolution sources. It has applications in medical imaging, surveillance, and entertainment.
  3. Colorization of Black and White Images: Techniques for adding color to black and white images, often used for restoring historical photos and improving the visual appeal of visual content.
  4. Image Enhancement for Medical Imaging: Research in this area is dedicated to developing specialized image processing techniques for improving the quality and diagnostic value of medical images such as X-rays, MRIs, and CT scans.
  5. HDR Imaging (High Dynamic Range): HDR techniques aim to capture and display a wider range of brightness levels in images, improving the visualization of scenes with varying lighting conditions, such as landscapes or architectural photography.
  6. Image Enhancement for Satellite and Remote Sensing: Specialized techniques are developed to enhance satellite and remote sensing imagery for applications in agriculture, environmental monitoring, and disaster management.
  7. Image Compression and Transmission: Research focuses on efficient methods for compressing and transmitting images without significant loss of quality, crucial for applications like video conferencing and image sharing on the internet.
  8. Image Deblurring: Techniques to remove blurriness caused by factors such as camera shake or motion, improving the sharpness and clarity of images.
  9. Image Segmentation and Object Recognition: These techniques involve separating objects from the background in images and recognizing individual objects or regions, vital for various computer vision applications.
  10. Deep Learning-Based Image Enhancement: Utilizing deep learning models for image enhancement tasks, such as generative adversarial networks (GANs) for realistic image synthesis and enhancement.

Image Processing and Enhancement research continues to advance, driven by the increasing demand for high-quality images in diverse fields such as healthcare, entertainment, agriculture, and more. Researchers in this area are constantly developing innovative solutions to enhance the visual content that surrounds us, ultimately improving our ability to interpret and utilize digital imagery in a variety of applications.

Object Detection and Recognition
Introduction Object Detection and Recognition: Object Detection and Recognition is a vibrant and evolving field of computer vision and artificial intelligence, dedicated to the automated identification and localization of objects
Image Processing and Enhancement
Introduction Image Processing and Enhancement: Image Processing and Enhancement is a pivotal domain within the realm of computer vision and digital imaging. This field is dedicated to the development of
Computer Vision for Robotics and Autonomous Systems
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