Prof Dr. Rosane Collevatti | Object Detection and Recognition | Best Researcher Award

Posted on by ScienceFather

Prof Dr. Rosane Collevatti, Object Detection and Recognition, Best Researcher Award

Rosane Collevatti at Universidade Federal de Goias, Brazil

Professional Profile

🌟 Summary:

Dr. Rosane Garcia Collevatti, born on December 2, 1968, in Brazil, is an Associate Professor Level 3 at Universidade Federal de Goiás. With a profound dedication to evolutionary ecology, she specializes in population genomics, phylogeography, and community phylogeny in the Neotropics. Through her leadership, she supervises a dynamic research group, mentors numerous students, and oversees multiple projects aimed at unraveling biodiversity dynamics.

🎓 Education:

  • Ph.D. in Ecology, Universidade de Brasília, Brazil, 2000
  • M.Sc. in Entomology-Ecology, Universidade Federal de Viçosa, Brazil, 1995
  • B.Sc. in Forest Engineering, Universidade Federal de Viçosa, Brazil, 1992

💼 Professional Experience

  • Associate Professor Level 3, Universidade Federal de Goiás, Brazil (February 2009 – Present)
  • Full Professor, Universidade Católica de Brasília, Brazil (February 2000 – January 2009)
  • Scientific Adviser, CNPq Scientific Adviser Committee for Forest Resources, Brazil (March 2018 – December 2020)
  • Visiting Researcher, University of Gothenburg (Sweden), INRA (France), Smithsonian Tropical Research Institute (Panama)
  • Coordinator, IUFRO Division 2.04 (Genetics), Austria (June 2024 – ongoing)

🔬 Research Interests:

  • Evolutionary ecology
  • Phylogenetics and phylogenomics
  • Phylogeography
  • Community phylogeny
  • Landscape genetics and ecology
  • Population genomics

📖 Publications Top Noted:

Paper Title: The effect of tree-on-tree interactions and abiotic conditions on woody communities in Brazilian savannas
  • Authors: Davi Borges Chagas, Alessandro Rapini, Pedro Manuel Villa, Rosane Garcia Collevatti
  • Journal: Journal of Tropical Ecology
  • Volume: 39
  • Issue: 4
  • Pages: 460-471
  • Year: 2023
Paper Title: Amount and isolation of aquatic habitat drive anuran diversity in agricultural landscapes in the Brazilian Cerrado
  • Authors: Priscila Silveira, Samanta Iop, Juliana Silveira dos Santos, Edgar L. Lima, Felipe Martello, Milton Cezar Ribeiro, Natan M. Maciel, Rosane G. Collevatti
  • Journal: Landscape Ecology
  • Volume: 38
  • Issue: 9
  • Pages: 1871-1885
  • Year: 2023
Paper Title: Integrating ecological niche and hydrological connectivity models to assess the impacts of hydropower plants on an endemic and imperilled freshwater turtle
  • Authors:André Luis Regolin, Raíssa Bressan, Tobias S. Kunz, Felipe Martello, Ivo R. Ghizoni‐Jr, Jorge José Cherem, Danilo José Vieira Capela, Luiz Gustavo R. Oliveira‐Santos, Rosane Garcia Collevatti, Thadeu Sobral‐Souza
  • Journal: Journal of Applied Ecology
  • Volume: 60
  • Issue: 3
  • Pages: 631-643
  • Year: 2023
Paper Title: Neogene–Quaternary tectonic, eustatic and climatic events shaped the evolution of a South American treefrog
  • Authors: Tatianne Piza Ferrari Abreu‐Jardim, Natácia Evangelista de Lima, Lucas Jardim, Natan Medeiros Maciel, Rafael Félix de Magalhães, Guarino Rinaldi Colli, Célio Fernando Baptista Haddad, Rosane Garcia Collevatti
  • Journal: Journal of Biogeography
  • Volume: 50
  • Issue: 5
  • Pages: 1142-1156
  • Year: 2023
Paper Title: High and similar genetic diversity in wild and cultivated populations of the economically important fruit tree Caryocar coriaceum Wittm. in Caatinga
  • Authors: Feng, Q., Zhou, J., Dong, N., Han, X., Zhang, B.
  • Journal: Quantitative Imaging in Medicine and Surgery
  • Volume: 14
  • Issue: 3
  • Pages: 2309-2320
  • Year: 2024

Assoc Prof Dr. Sinong Quan | Object Detection and Recognition | Best Researcher Award

Posted on by ScienceFather

Assoc Prof Dr. Sinong Quan, Object Detection and Recognition, Best Researcher Award

Sinong Quan at National University of Defense Technology, China

Professional Profile

 

🎓 Education:

  • Assoc. Prof. Dr. Sinong Quan received his Ph.D. degree in Information and Communication Engineering from the National University of Defense Technology, Changsha, China, in 2019.

💼 Current Position:

He is currently an Associate Professor with the College of Electronic Science and Technology at the National University of Defense Technology.

🏆 Awards and Recognitions:

  • National Postdoctoral Innovative Talent Support Program Award (2022)
  • First-Class Science and Technology Progress Award from the Ministry of Education (2022)
  • Second-Class Nature Science Award from the Chinese Institute of Electronics (2021)
  • Outstanding Doctoral Dissertation of the PLA (2021)
  • Outstanding Master Dissertation of Hunan Province (2018)

🔬 Research Interests:

His research interests span imaging radar countermeasure and recognition, polarimetric radar information processing, target detection, pattern recognition, and machine learning.

 

Publications Top Noted:

Paper Title: Nearshore Ship Detection in PolSAR Images by Integrating Superpixel-Level GP-PNF and Refined Polarimetric Decomposition
  • Authors: Shujie Wu, Wei Wang, Jie Deng, Sinong Quan, Feng Ruan, Pengcheng Guo, Hongqi Fan
  • Journal: Remote Sensing
  • Volume: 16
  • Issue: 6
  • Year: 2024
Paper Title: Shadow-Based False Target Identification for SAR Images
  • Authors: Haoyu Zhang, Sinong Quan, Shiqi Xing, Junpeng Wang, Yongzhen Li, Ping Wang
  • Journal: Remote Sensing
  • Volume: 15
  • Issue: 21
  • Year: 2023
Paper Title: Ballistic limit evolution of field-aged flexible multi-ply UHMWPE-based composite armour inserts
  • Authors: Yancui Duan, Sinong Quan, Hui Fan, Zhenhai Xu, Shunping Xiao
  • Journal: Remote Sensing
  • Volume: 15
  • Issue: 18
  • Year: 2023
Paper Title: Near-Field 3D Sparse SAR Direct Imaging with Irregular Samples
  • Authors: Shiqi Xing, Shaoqiu Song, Sinong Quan, Dou Sun, Junpeng Wang, Yongzhen Li
  • Journal: Remote Sensing
  • Volume: 14
  • Issue: 24
  • Year: 2022
Paper Title: Near Field 3-D Millimeter-Wave SAR Image Enhancement and Detection with Application of Antenna Pattern Compensation
  • Authors: Shaoqiu Song, Jie Lu, Shiqi Xing, Sinong Quan, Junpeng Wang, Yongzhen Li, Jing Lian
  • Journal: Sensors
  • Volume: 22
  • Issue: 12
  • Year: 2022

Victor-Klaba-Object Detection and Recognition-Best Researcher Award 

Posted on by ScienceFather

Mr. Victor-Klaba-Object Detection and Recognition-Best Researcher Award 

University of Franche-Comté-France 

Author Profile

Early Academic Pursuits

Mr. Victor Klaba's academic journey in hydrogeology began with his Bachelor's degree in Earth Sciences from the University of Franche-Comté, Besançon, France. He continued his education with a Master's degree in the same field, specializing in structural geology and hydrodynamics. Currently, he is pursuing a Ph.D. in Hydrogeology at the University of Franche-Comté, focusing on the TRANSKARST project. His academic background has equipped him with a strong foundation in geological sciences and hydrogeological principles, preparing him for a career in understanding and managing water resources.

Professional Endeavors

Throughout his academic journey, Mr. Victor Klaba has gained valuable professional experiences in hydrogeology. As a Ph.D. student involved in the TRANSKARST project at the Chrono-environment Laboratory, he is dedicated to developing a multidisciplinary approach to improve understanding of the Arcier hydrosystem. Additionally, he has contributed to the COREAUNA project as an intern at the Geological Survey of New Caledonia, focusing on the geochemical characterization of the Koné alluvial aquifer. Victor's internships and research engagements have allowed him to apply theoretical knowledge in practical settings, honing his skills in fieldwork, laboratory analysis, and geological modeling.

Contributions and Research Focus

Mr. Victor Klaba's research focuses on the hydrogeological dynamics of karst systems, particularly the Arcier hydrosystem and the Montfaucon anticline. His work involves rigorous geological analysis, hydrochemical characterization, and hydrodynamic modeling to understand groundwater circulation and resource management. By studying these complex hydrogeological objects, Victor aims to contribute to the development of effective water resource protection policies and sustainable management strategies. His expertise in geomodelling software such as MODFLOW and KARSTMOD enables him to conduct sophisticated analyses and simulations to address pressing hydrogeological challenges.

Accolades and Recognition

While Mr. Victor Klaba's career is still in its early stages, his dedication and contributions to hydrogeological research have already been recognized by his peers and mentors. His involvement in the TRANSKARST project and other research initiatives demonstrates his commitment to advancing knowledge in the field of hydrogeology. As he continues to make strides in his research, Victor is poised to receive further accolades and recognition for his contributions to hydrogeological science and water resource management.

Impact and Influence

Mr. Victor Klaba's work in hydrogeology has the potential to have a significant impact on society and the environment. By studying karst systems, which serve as critical drinking water resources for a large portion of the global population, Victor's research directly contributes to addressing pressing issues related to water scarcity and quality. His findings and recommendations have the potential to inform policy decisions and management practices, ensuring the sustainable use and protection of groundwater resources for future generations.

The Object Detection and Recognition Award celebrates individuals who have demonstrated outstanding achievements in advancing the field of computer vision through innovative research and practical applications. This prestigious award recognizes researchers and technologists who have made significant contributions to the development of algorithms, methodologies, and systems for detecting and recognizing objects in images and videos.

Legacy and Future Contributions

As Mr. Victor Klaba continues his academic and professional journey in hydrogeology, his legacy will be defined by his contributions to advancing knowledge and understanding in the field. Through his research, he seeks to address complex hydrogeological challenges and develop innovative solutions for sustainable water resource management. By integrating multidisciplinary approaches and leveraging advanced modeling techniques, Victor aims to leave a lasting impact on hydrogeological science and contribute to the development of effective strategies for safeguarding water resources in a changing world.

Notable Publication

Nadia-AL Rousan-Applications of Computer Vision-Best Researcher Award 

Posted on by ScienceFather

Dr. Nadia-AL Rousan-Applications of Computer Vision-Best Researcher Award 

German Jordanian University-Jordan

Author Profile

Early Academic Pursuits

Dr. Nadia AL-Rousan embarked on her academic journey with a strong focus on computer engineering and artificial intelligence. Her passion for these fields led her to pursue a Ph.D. in Computer Engineering with a specialization in Artificial Intelligence. During her formative years, she developed a wide array of skills encompassing artificial intelligence, data encryption, computer networks, information security, and renewable energy. This diverse educational background laid the foundation for her future endeavors in research and academia.

Professional Endeavors

As an accomplished assistant professor, Dr. Nadia AL-Rousan has dedicated over twelve years to teaching and research across various esteemed institutions worldwide. Her teaching portfolio includes a diverse range of courses, spanning computer networks, information technology, artificial intelligence, machine learning, advanced neural networks, deep learning, and expert systems. This extensive experience has not only shaped her teaching methodology but also deepened her understanding of these critical fields.

Contributions and Research Focus

Dr. Nadia AL-Rousan's research focus spans multiple domains within computer engineering and artificial intelligence. Her expertise includes artificial intelligence, data encryption, data concealment, computer networks, information security, data science, and renewable energy. She is particularly interested in the intersection of artificial intelligence and cybersecurity, developing innovative solutions to safeguard sensitive information in digital environments. Additionally, her research in renewable energy demonstrates her commitment to leveraging technology for sustainable development.

Accolades and Recognition

Dr. Nadia AL-Rousan's contributions to the field have earned her significant recognition, both nationally and internationally. In 2022, she was classified as one of the top ten women working in technology globally, specifically in the category of artificial intelligence. This prestigious acknowledgment underscores her exceptional contributions to the field and her role as a leading figure in AI research and application. Furthermore, she was honored with the WomenTech Global AI Inclusion Award, recognizing her efforts to promote diversity and inclusion within the tech industry.

Impact and Influence

Beyond her research and academic achievements, Dr. Nadia AL-Rousan's impact extends to her role as an ambassador for the WomenTeck network. Through her advocacy and mentorship, she has inspired countless individuals, particularly women, to pursue careers in technology. Her involvement in various academic networks and professional organizations further amplifies her influence, promoting diversity and inclusion within the tech industry.

The Applications of Computer Vision Award recognizes individuals who have demonstrated outstanding contributions to the field of computer vision through innovative research and impactful applications. This prestigious award celebrates researchers who have pushed the boundaries of computer vision technology, unlocking new possibilities in various domains such as image recognition, object detection, video analysis, and autonomous vehicles.

Legacy and Future Contributions

Looking ahead,Dr. Nadia AL-Rousan remains committed to advancing her research in artificial intelligence, cybersecurity, and renewable energy. She aims to explore new frontiers in AI-driven solutions, addressing emerging challenges in data security and sustainable technology development. As she continues to push the boundaries of knowledge and inspire the next generation of technologists, her work will undoubtedly leave a lasting impact on the field of computer engineering and artificial intelligence.

Dr. Nadia AL-Rousan's career exemplifies the profound impact that dedicated individuals can have on advancing technology and fostering inclusivity within the industry. Her multifaceted expertise and unwavering commitment to her fields of study position her as a leading figure in contemporary technology research, shaping the future of AI and cybersecurity.

Citations   

  • Citations    901
  • h-index        13
  • i10-index     16

Notable Publication

Object Detection and Recognition

Posted on by ScienceFather

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 within digital images or videos. This area of research plays a pivotal role in various applications, ranging from autonomous vehicles and robotics to surveillance systems and medical image analysis.

Subtopics in Object Detection and Recognition:

  1. Deep Learning-Based Object Detection: This subfield focuses on the development of deep neural networks for precise object detection in complex scenes. Techniques like Faster R-CNN, YOLO, and SSD have revolutionized this area, achieving state-of-the-art results.
  2. Instance Segmentation: Going beyond object detection, instance segmentation aims to not only detect objects but also distinguish between individual instances of the same object category within an image, providing pixel-level segmentation masks.
  3. Real-time Object Detection: Research in this subtopic is concerned with the optimization of object detection models to operate in real-time, making them suitable for applications like self-driving cars and live video analysis.
  4. Transfer Learning and Pre-trained Models: Leveraging pre-trained models and transfer learning techniques is crucial for improving the efficiency and accuracy of object detection systems, especially when dealing with limited datasets.
  5. 3D Object Detection: This emerging subfield extends object detection to the three-dimensional space, enabling the detection and localization of objects in 3D environments, which is essential for applications like augmented reality and autonomous navigation.
  6. Multi-Object Tracking: Object detection isn't limited to identifying objects in a single frame; multi-object tracking involves maintaining the identity and trajectory of objects across multiple frames in video sequences.
  7. Small Object Detection: Addressing the challenge of detecting small objects, which can be particularly relevant in medical imaging, satellite imagery, and surveillance where objects of interest are often tiny.
  8. Adversarial Attacks and Robustness: Research in this subtopic focuses on making object detection models more robust against adversarial attacks, which are manipulations of input data designed to deceive the model.
  9. Domain Adaptation for Object Detection: Developing techniques to adapt object detection models to new domains or datasets, a crucial aspect for real-world applications with changing environmental conditions.
  10. Human-Object Interaction Recognition: Combining object detection with human pose estimation to recognize interactions between humans and objects, allowing for a deeper understanding of human behavior in scenes.

These subtopics reflect the diverse and dynamic nature of Object Detection and Recognition research, addressing various challenges and pushing the boundaries of what is possible in computer vision applications. Researchers in this field continually strive to improve the accuracy, efficiency, and robustness of object detection systems to meet the demands of real-world scenarios.

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
Introduction of Computer Vision for Robotics and Autonomous Introduction: Computer Vision for Robotics and Autonomous Systems is a multidisciplinary field at the intersection of computer vision, robotics, and artificial intelligence.
3D Computer Vision
Introduction of 3D Computer Vision 3D Computer Vision is a dynamic and interdisciplinary field that aims to enable machines to perceive and understand the three-dimensional structure of the world from
Medical Image Analysis
Introduction of Medical Image Analysis Medical Image Analysis is a critical and rapidly evolving field that harnesses the power of computer vision and machine learning to extract valuable insights from
Video Analysis
Introduction of Video Analysis Video Analysis and Understanding is a dynamic and interdisciplinary field that aims to develop algorithms and techniques for extracting meaningful information from video data. It plays
Deep Learning for Computer Vision
Introduction of Deep Learning for Computer Vision Deep Learning for Computer Vision is at the forefront of modern artificial intelligence, revolutionizing the way machines perceive and interpret visual information. It
Applications of Computer Vision
Introduction of Applications of Computer Vision Applications of Computer Vision represent a diverse and ever-expanding landscape of practical uses for visual data analysis and interpretation. Computer vision technology has transitioned
Human-Computer Interaction
Introduction of Human-Computer Interaction Introduction: Human-Computer Interaction (HCI) research is a multidisciplinary field that focuses on understanding and improving the interaction between humans and technology. It explores how users interact
Biometrics and Security
Introduction of Biometrics and Security Biometrics and Security research is dedicated to the development of cutting-edge technologies that leverage unique physiological or behavioral characteristics of individuals for identity verification and