Shujiao Liao | Machine Learning | Best Researcher Award

Prof . Shujiao Liao | Machine Learning | Best Researcher Award

Professor at Minnan Normal University, China

Dr. Shujiao Liao is a full professor at the School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, Fujian, China. With a strong academic background in applied mathematics and software engineering, she has dedicated her career to advancing the fields of granular computing, data mining, and machine learning. Her work bridges theoretical mathematics and computational methodologies, enabling novel approaches to intelligent data analysis. Over the years, Dr. Liao has played a pivotal role in both academic teaching and research leadership, contributing significantly to her institution’s development and scholarly output. She has guided numerous students and collaborated across interdisciplinary research groups. Her commitment to innovation and academic excellence makes her a respected figure in her field. As a scholar deeply engaged in cutting-edge technologies and data science trends, she continues to contribute impactful research and strives to address complex problems with analytical precision and computational insight.

Professional Profile 

Education🎓

Dr. Shujiao Liao holds a strong interdisciplinary educational background that underpins her academic career. She earned her Master of Science degree in Applied Mathematics from Shantou University, Guangdong, China, in 2006, where she built a solid foundation in mathematical modeling and analytical reasoning. Her pursuit of advanced studies led her to obtain a Ph.D. degree in Software Engineering from the University of Electronic Science and Technology of China, Chengdu, Sichuan, in 2018. This advanced degree enabled her to integrate mathematical theory with practical software systems, contributing to her versatility in computational research. Her doctoral studies focused on bridging data-centric algorithms with intelligent systems, which now form the core of her research interests. This rich educational trajectory has allowed her to approach complex scientific questions from both a mathematical and engineering perspective, making her academic contributions particularly robust in the fields of data mining and machine learning.

Professional Experience📝

Dr. Shujiao Liao is currently a full professor at the School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, Fujian, China. With an academic career that spans over a decade, she has demonstrated excellence in teaching, research, and academic leadership. In her current role, she teaches advanced mathematics and computational theory courses, supervises postgraduate research projects, and actively engages in departmental development. She has led several internal and collaborative research initiatives in granular computing and machine learning, working closely with both academic and industrial partners. Her experience also includes conference presentations, curriculum development, and cross-disciplinary project coordination. She is recognized for her effective mentorship, contributing to the growth of young researchers and promoting high standards in academic inquiry. Through her consistent professional contributions, Dr. Liao has helped elevate her institution’s research standing and continues to serve as a vital resource for the academic community in mathematics and software research.

Research Interest🔎

Dr. Shujiao Liao’s research interests span several pivotal domains in computer science and applied mathematics, with a particular focus on granular computing, data mining, and machine learning. Her work in granular computing explores how knowledge can be structured and processed using information granules, improving the interpretability and efficiency of decision-making systems. In the area of data mining, she investigates algorithms for pattern discovery, classification, and clustering, contributing to improved data-driven strategies in scientific and industrial applications. Her interests in machine learning include developing intelligent models capable of adaptive learning and robust performance across complex datasets. Dr. Liao’s research bridges theory and application, aiming to solve real-world problems such as intelligent diagnostics, automated reasoning, and big data analysis. Her interdisciplinary focus allows her to work on innovative projects that combine mathematical rigor with computational techniques, positioning her as a contributor to the evolving field of intelligent systems and artificial intelligence.

Award and Honor🏆

While specific awards and honors for Dr. Shujiao Liao were not provided in the given information, her appointment as a full professor reflects recognition of her academic contributions and research leadership. Attaining such a role typically involves competitive peer-reviewed evaluations, consistent scholarly output, and excellence in teaching and mentorship. It is likely that she has received internal university-level commendations, research project funding awards, or participation in prestigious academic panels, common among professors of her standing. If available, details such as Best Paper Awards, Research Excellence Awards, or National Science Grants would further highlight her academic acclaim. Her long-standing role in the academic community and sustained focus on impactful research suggest she is a strong candidate for further honors at national or international levels. Formal acknowledgment through such accolades would complement her already impressive academic and research credentials, reinforcing her eligibility for broader recognitions such as the Best Researcher Award.

Research Skill🔬

Dr. Shujiao Liao possesses a robust set of research skills grounded in both theoretical understanding and practical application. She demonstrates strong expertise in mathematical modeling, algorithm development, and data analysis, which are essential for her work in granular computing and data mining. Her proficiency in applying machine learning techniques to complex datasets enables her to design predictive models with real-world relevance. She is adept at academic writing, literature review, and hypothesis-driven exploration, essential for high-quality publications and grant writing. Additionally, Dr. Liao has strong collaborative and project management skills, allowing her to lead interdisciplinary research teams and coordinate joint research initiatives. Her experience in supervising graduate theses further reflects her ability to guide rigorous research methodologies. She is also likely skilled in programming languages and tools used in data science, such as Python, MATLAB, or R, further supporting her contributions to computational research domains.

Conclusion💡

Dr. Shujiao Liao is a strong candidate for the Best Researcher Award, particularly within fields like granular computing and machine learning. Her academic background and full professorship position suggest a high level of expertise and leadership. To solidify her candidacy for top-tier recognition, showcasing quantifiable research outcomes, international influence, and broader impact will be important.

Publications Top Noted✍

  • Title: WrdaGAN: A text-to-image synthesis pipeline based on Wavelet Representation and Adaptive Sample Domain Constraint strategy
    Authors: Yongchao Qiao, Ya’nan Guan, Shujiao Liao, Wenyuan Yang, Weiping Ding, Lin Ouyang
    Year: 2025
    Citation: DOI: 10.1016/j.engappai.2025.111305

  • Title: Semisupervised Feature Selection With Multiscale Fuzzy Information Fusion: From Both Global and Local Perspectives
    Authors: Nan Zhou, Shujiao Liao, Hongmei Chen, Weiping Ding, Yaqian Lu
    Year: 2025
    Citation: DOI: 10.1109/TFUZZ.2025.3540884

  • Title: S-approximation spaces extension model based on item-polytomous perspective
    Authors: Xiaojie Xie, Shujiao Liao, Jinjin Li
    Year: 2024
    Citation: DOI: 10.21203/rs.3.rs-4447331/v1

  • Title: Multi-Target Rough Sets and Their Approximation Computation with Dynamic Target Sets
    Authors: Wenbin Zheng, Jinjin Li, Shujiao Liao
    Year: 2022
    Citation: DOI: 10.3390/info13080385

  • Title: Multi-Label Attribute Reduction Based on Neighborhood Multi-Target Rough Sets
    Authors: Wenbin Zheng, Jinjin Li, Shujiao Liao, Yidong Lin
    Year: 2022
    Citation: DOI: 10.3390/sym14081652

  • Title: Attribute‐scale selection for hybrid data with test cost constraint: The approach and uncertainty measures
    Authors: Shujiao Liao, Yidong Lin, Jinjin Li, Huiling Li, Yuhua Qian
    Year: 2022
    Citation: DOI: 10.1002/int.22678

  • Title: Feature–granularity selection with variable costs for hybrid data
    Authors: Shujiao Liao, Qingxin Zhu, Yuhua Qian
    Year: 2019
    Citation: DOI: 10.1007/s00500-019-03854-2

Prof. Dr. Shaofeng Shao | AI-driven Material Discovery | Best Researcher Award

Prof. Dr. Shaofeng Shao | AI-driven Material Discovery | Best Researcher Award

Nanjing University of Information Science and Technology, China

👨‍🎓 Profiles

Scopus

Publications

Harnessing Transfer Deep Learning Framework for the Investigation of Transition Metal Perovskite Oxides with Advanced p-n Transformation Sensing Performance

  • Authors: S. Shao, Shaofeng; L. Yan, Liangwei; J. Li, Jiale; H.W. Kim, Hyoun Woo; S.S. Kim, Sang Sub
    Journal: ACS Sensors
    Year: 2025

Language Model-Assisted Machine Learning, Photoelectrochemical, and First-Principles Investigation of Compatible Solvents for a CH3NH3PbI3 Film in Water

  • Authors: Y. Huang, Yiru; S. Li, Shenyue; W. Hu, Wenguang; Q. Li, Qingfang; L. Zhang, Lei
    Journal: ACS Applied Materials and Interfaces
    Year: 2024

Data-driven exploration of terbium-doped tungsten oxide for Ultra-Precise detection of 3H-2B: Implications for gas sensor applications

  • Authors: S. Shao, Shaofeng; L. Yan, Liangwei; L. Zhang, Lei; H.W. Kim, Hyoun Woo; S.S. Kim, Sang Sub
    Journal: Chemical Engineering Journal
    Year: 2024

Ionic liquid-assisted preparation of Ag–Zn–In–S quaternary quantum dot thin films and luminescence performance optimized by machine learning

  • Authors: S. Wei, Song; X. Luo, Xiang; S. Shao, Shaofeng; L. Zhang, Lei
    Journal: Dyes and Pigments
    Year: 2024

Mr. Mohammad Hussein Amiri | Artificial Intelligence | Best Researcher Award

Mr. Mohammad Hussein Amiri | Artificial Intelligence | Best Researcher Award

Mohammad Hussein Amiri at Shahid Beheshti University, Iran

👨‍🎓 Profiles

Scopus

Orcid

An innovative data-driven AI approach for detecting and isolating faults in gas turbines at power plants

  • Authors: Mohammad Hussein Amiri, Nastaran Mehrabi Hashjin, Maryam Khanian Najafabadi, Amin Beheshti, Nima Khodadadi
    Journal: Expert Systems with Applications
    Year: 2025

Hippopotamus optimization algorithm: a novel nature-inspired optimization algorithm

  • Authors: Mohammad Hussein Amiri, Nastaran Mehrabi Hashjin, Montazeri, M., Mirjalili, S., Nima Khodadadi
    Journal: Scientific Reports
    Year: 2024

Monitoring UAV status and detecting insulator faults in transmission lines with a new classifier based on aggregation votes between neural networks by interval type-2 TSK fuzzy system

  • Authors: Mohammad Hussein Amiri, Mahdi Pourgholi, Nastaran Mehrabi Hashjin, Mohammadreza Kamali Ardakani
    Journal: Soft Computing
    Year: 2024

Novel hybrid classifier based on fuzzy type-III decision maker and ensemble deep learning model and improved chaos game optimization

  • Authors: Nastaran Mehrabi Hashjin, Mohammad Hussein Amiri, Ardashir Mohammadzadeh, Seyedali Mirjalili, Nima Khodadadi
    Journal: Cluster Computing
    Year: 2024

Monitoring UAV Status and Detecting Insulation Defects in Transmission Lines with a New Hybrid Classifier based on the Type-2 Fuzzy and Neural Networks

  • Authors: Mohammad Hussein Amiri, Mahdi Pourgholi, Nastaran Mehrabi Hashjin, Mohammadreza Kamali Ardakani
    Journal: Research Square
    Year: 2023

Prof. Igor Belenichev | Machine Learning | Excellence in Innovation

Prof. Igor Belenichev | Machine Learning | Excellence in Innovation

Professor at Zaporizhzhia State Medical University, Ukraine

Profiles

Scopus

Orcid

Google Scholar

📚 Summary

Prof. Igor Fedorovich Belenichev is a distinguished Full Professor and Head of the Department of Pharmacology and Medical Formulation at Zaporizhzhia State Medical University. Renowned for his innovative research in neuroprotection and pharmacology, he is a laureate of the Cabinet of Ministers of Ukraine Prize for the development and implementation of groundbreaking technologies.

Education

  • Zaporizhzhia State Medical Institute (1988): Graduated with a degree in medicine.
  • Postgraduate studies (1988), professor assistant (1991), senior teacher (1999), associate professor (2004), and full professor (2006).

💼 Professional Experience

  • Zaporizhzhia State Medical University: Head of the Department of Pharmacology and Medical Formulation since 2005.
  • Main Scientific Researcher at «Pharmatrone» (since 1993).
  • Head of the regional branch of the Association of Pharmacologists of Ukraine.
  • Co-worker of the regional group of the National Expert Centre of the Ministry of Health of Ukraine.

🔬 Research Interests

Prof. Belenichev’s research focuses on the molecular and biochemical mechanisms of ischemic brain damage and the development of effective neuroprotectors. His work explores the roles of reactive oxygen and nitrogen species, thiol-disulfide systems, pro-/anti-apoptotic proteins, estrogen receptors, and endogenous neuroprotection factors. He also investigates drugs for CNS pathologies and effective neuro- or cardioprotectors from derivatives of 1,2,4-triazole, chinazoline, and xanthine.

🏆 Achievements

  • Scientific Works: Authored and co-authored 715 scientific publications.
  • Patents: Holder of 182 patents in Ukraine and the Russian Federation.
  • Theses: Supervised 3 Dr. Habs and 7 Ph.D. theses.
  • Drug Development: Contributed to the creation of drugs like Thiotriazoline, Thiocetam, and Thiodarone.
  • Awards: Token of the Bibliographical Society of America (2003), Regional Program “Zoryaniy Shlyakh” Prize (2000), and Cabinet of Ministers of Ukraine Prize (2017).

 

Publications

5+1-Heterocyclization as preparative approach for carboxy-containing triazolo[1,5-c]quinazolines with anti-inflammatory activity

  • Authors: Krasovska, Natalya; Berest, Galina; Belenichev, Igor; Severina, Hanna; Nosulenko, Inna; Voskoboinik, Oleksii; Okovytyy, Sergiy; Kovalenko, Serhii
  • Journal: European Journal of Medicinal Chemistry
  • Year: 2024

Beta-Blockers of Different Generations: Features of Influence on the Disturbances of Myocardial Energy Metabolism in Doxorubicin-Induced Chronic Heart Failure in Rats

  • Authors: Igor Belenichev; Olexiy Goncharov; Nina Bukhtiyarova; Oleh Kuchkovskyi; Victor Ryzhenko; Lyudmyla Makyeyeva; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Biomedicines
  • Year: 2024

Characteristics of HIF-1α and HSP70 mRNA Expression, Level, and Interleukins in Experimental Chronic Generalized Periodontitis

  • Authors: Parkhomenko Daria; Igor Belenichev; Kuchkovskyi Oleh; Ryzhenko Victor
  • Journal: MicroRNA
  • Year: 2024

Comparative Analysis of the Effect of Beta Blockers of Different Generations on the Parameters of Myocardial Energy Metabolism in Experimental Doxorubicin-Induced Chronic Heart Failure

  • Authors: Igor Belenichev; Olexiy Goncharov; Nina Bukhtiyarova; Oleh Kuchkovskyi; Victor Ryzhenko; Lyudmyla Makyeyeva; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Preprint
  • Year: 2024

Development and Optimization of Nasal Composition of a Neuroprotective Agent for Use in Neonatology after Prenatal Hypoxia

  • Authors: Igor Belenichev; Olena Aliyeva; Bogdan Burlaka; Kristina Burlaka; Oleh Kuchkovskyi; Dmytro Savchenko; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Pharmaceuticals
  • Year: 2024

Prof. Hua Zhang | Machine Learning | Best Researcher Award

Prof. Hua Zhang | Machine Learning | Best Researcher Award

Professor at Wuhan University of Science and Technology, China

Profiles

Scopus

Research Gate

Summary:

Prof. Hua Zhang is a distinguished professor at Wuhan University of Science and Technology (WUST), specializing in clean steel production technology, numerical simulation, and the development of iron-based amorphous alloys. With a Ph.D. in Metallurgical Engineering, he has made significant contributions to steelmaking technology, securing multiple prestigious awards, including provincial science and technology awards and the Baosteel Outstanding Teacher Award. As the vice dean of the School of Materials Science at WUST, Dr. Zhang has published over 100 papers and holds numerous patents.

Education

  • Ph.D. in Metallurgical Engineering (2012)

💼 Professional Experience

  • Professor, Wuhan University of Science and Technology (2019–Present)
  • Postdoctoral Researcher, MCC Continuous Casting Technology Engineering Co., Ltd. (2015–2017)
  • Vice Dean, School of Materials Science, WUST

🔬 Research Interests

  • Clean steel production technology
  • Continuous casting new technology
  • Numerical simulation
  • Iron-based amorphous soft magnetic alloys
  • Secondary utilization of metallurgical resources

 

Publications

Modulating Fe/P Ratios in Fe-P Alloy through Smelting Reduction for Long-Term Electrocatalytic Overall Water Splitting

  • Authors: Zhang, T., Ren, X., Mo, S., Zhang, H., Ni, H.
  • Journal: Journal of Materials Science and Technology
  • Year: 2024
  • Authors: Li, J., Wu, G., Fang, Q., Zhang, H., Ni, H.
  • Journal: Journal of the Taiwan Institute of Chemical Engineers
  • Year: 2024

Investigation on the Characteristics of Porosity, Melt Pool in 316L Stainless Steel Manufactured by Laser Powder Bed Fusion

  • Authors: Liu, C.-S., Xue, X., Wang, Y., Xiong, L., Ni, H.-W.
  • Journal: Journal of Materials Research and Technology
  • Year: 2024

Suppression of Free-Surface Vortex in Tundish by Rotating Stopper-Rod and Its Impact on Multiphase Flow in Mold

  • Authors: Huang, K., Zhang, H., Lu, P., Fang, Q., Ni, H.
  • Journal: Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science
  • Year: 2024

Optimization of Multiphase Flow and Initial Solidification Behaviors in a Stainless Steel Mold by SEN Design

  • Authors: Gao, F., Fang, Q., Zha, W., Zhang, H., Ni, H.
  • Journal: Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science
  • Year: 2024

Dr. Kais Iben Nassar | Machine Learning | Best Researcher Award

Dr. Kais Iben Nassar | Machine Learning | Best Researcher Award

Doctorate at University of Aveiro , Portugal

Profiles

Scopus

Orcid

Google Scholar

Academic Background

Dr. Kais Iben Nassar is a researcher with a focus on Condensed Matter Physics and Computational Chemistry. He completed his PhD in Physics of Condensed Materials in 2022 through a joint program between the University of Aveiro, Portugal, and the University of Sfax, Tunisia. Dr. Nassar is renowned for his work in materials science, particularly in the study of 2D materials like MXenes and their applications in energy storage and catalysis.

Education

  • PhD in Physics of Condensed Materials
    Université de Sfax & Universidade de Aveiro (2022)
    Achieved with highest honors.
  • Master’s in Condensed Matter Physics
    Université de Sfax (2018)
    Graduated with distinction.
  • Fundamental License in Physics-Chemistry
    Université de Sfax (2016)
    Graduated with distinction.

Professional Experience

  • Postdoctoral Researcher
    Universidade de Aveiro, CICECO (2023 – Present)
    Focus on MXenes catalysts and computational chemistry.
  • Researcher
    Université de Sfax & Universidade de Aveiro (2018 – 2021)
    Conducted research on perovskites and materials science.
  • Invited Assistant Professor
    Université de Sfax (2021 – 2022)
    Taught and mentored students in physics and chemistry.

🔬 Research Interests

Dr. Nassar’s research interests encompass Condensed Materials Physics, nano-materials, computational chemistry, and machine learning. His work includes investigating the properties of 2D materials such as MXene, exploring their potential in energy storage, catalysis, and electronics. He is actively engaged in the preparation and characterization of new perovskite ceramics and the study of their structural, electrical, and magnetic properties. Dr. Nassar is also a member of the European Materials Acceleration Center for Energy (EU-MACE) under the COST Action CA22123.

 Publications

Tailoring of structural, morphological, electrical, and magnetic properties of LaMn1−xFexO3 ceramics
  • Authors: Thakur, P., Nassar, K.I., Kumar, D., Essid, M., Lal, M.
  • Journal: RSC Advances
  • Year: 2024
Structural, electrical properties of bismuth and niobium-doped LaNiO3 perovskite obtained by sol–gel route for future electronic device applications
  • Authors: Nassar, K.I., Benamara, M., Kechiche, L., Teixeira, S.S., Graça, M.P.F.
  • Journal: Indian Journal of Physics
  • Year: 2024
Investigating Fe-doped Ba0.67Ni0.33Mn1−xFexO3 (x = 0, 0.2) ceramics: insights into electrical and dielectric behaviors
  • Authors: Tayari, F., Iben Nassar, K., Algessair, S., Hjiri, M., Benamara, M.
  • Journal: RSC Advances
  • Year: 2024
Sol–gel synthesized (Bi0.5Ba0.5Ag)0.5 (NiMn)0.5O3 perovskite ceramic: An exploration of its structural characteristics, dielectric properties and electrical conductivity
  • Authors: Tayari, F., Iben Nassar, K., Benamara, M., Soreto Teixeira, S., Graça, M.P.F.
  • Journal: Ceramics International
  • Year: 2024
Study of Electrical and Dielectric Behaviors of Copper-Doped Zinc Oxide Ceramic Prepared by Spark Plasma Sintering for Electronic Device Applications
  • Authors: Benamara, M., Iben Nassar, K., Rivero-Antúnez, P., Serrà, A., Esquivias, L.
  • Journal: Nanomaterials
  • Year: 2024

Mr. Siphumelele Zondi | Artificial Intelligence | Best Researcher Award

Mr. Siphumelele Zondi, Artificial Intelligence, Best Researcher Award

Siphumelele Zondi at Durban University of Technology, South Africa

Professional Profile

🌟 Summary:

Mr. Bhekani Siphumelele Zondi is a charismatic media practitioner, journalist, academic, content lead, and media researcher. With extensive experience in technology, social media, television, online, and radio programming, Zondi has significantly impacted South Africa’s media landscape.

🎓 Education:

  • Master of Arts in Media and Cultural Studies
    • University of Sussex, England (2012 – 2013)
    • Research: Social Media as the New Public Sphere
  • Bachelor of Technology in Journalism
    • Tshwane University of Technology, South Africa (Received Dec 2005)
    • Major: Broadcast Journalism

💼 Professional Experience:

  • Durban University of Technology (DUT)
    • Journalism Lecturer (2019 – Present)
    • Creator & Content Lead, Credible Source by DUT Journalism (2023 – Present)
  • South African Broadcasting Corporation (SABC)
    • Creator, Senior Producer & Presenter: Network (2013 – March 2024)
    • Presenter: Africa Digest (April 2013 – February 2019)
  • CNBC Africa
    • Senior Producer & Presenter (April 2013 – July 2013)
  • Tshwane University of Technology (TUT)
    • Journalism Lecturer (August 2009 – September 2011)
  • e-TV
    • Television News Reporter (April 2005 – September 2006)

🔬 Research Interests:

  • Social Media Engagement
  • Interactions between Politicians, Journalists, and Audiences
  • Use of Artificial Intelligence in Journalism

🏆 Awards & Recognitions:

  • 2017: Mail & Guardian Top 200 Young South Africans
  • 2011: Chevening Scholarship from the British Council
  • 2010: Blog of the Year Award Nomination – Journ’Tau
  • 2008: SABC News Awards Nomination – Best Current Affairs Presenter

🌐 Fellowships:

  • 2010/11: Finland EVA Junior Fellow
  • 2007: Member of Finland Foreign Correspondents’ Programme

📖 Publications Top Noted:

Paper Title: The Role of Artificial Intelligence in Contemporary Journalism Practice in Two African Countries
  • Authors: Siphumelele Zondi, Theodora Adjin-Tettey, Tigere Muringa, Samuel Danso
  • Journal: Media and Journalism
  • Year: 2024

Mr. Xiaoyu Li | Deep Learning | Best Researcher Award

Mr. Xiaoyu Li, Deep Learning, Best Researcher Award

Xiaoyu Li at Beijing Forestry University, China

Professional Profile

🌟 Summary:

Xiaoyu Li is a university student at Beijing Forestry University’s School of Soil and Water Conservation. His research focuses on Remote Sensing & GIS, Image Processing, Land Use, Transportation, UAV utilization, and Ecology. He has contributed to national-level scientific projects, including the Qinghai-Tibet Plateau expedition, and has authored publications in prestigious journals. His work includes assessing human living environments, controlling soil erosion, and studying sediment connectivity and erosion dynamics. Xiaoyu Li has pioneered large-scale land use classification in northwestern China using UAV remote sensing and has contributed to understanding vegetation changes in the Qinghai-Tibet Plateau.

🎓 Education:

Currently pursuing studies at Beijing Forestry University, College of Soil and Water Conservation.

💼 Professional Experience:

Engaged in multiple national-level research projects focusing on environmental assessment, soil erosion control, and watershed dynamics.

🔬 Research Interests:

  • Remote Sensing & GIS
  • Image Processing and Analysis
  • Land Use and Transportation
  • UAV (drone) utilization and Ecology

📖 Publications Top Noted:

Paper Title: Land-Use Composition, Distribution Patterns, and Influencing Factors of Villages in the Hehuang Valley, Qinghai, China, Based on UAV Photogrammetry
  • Authors: Xiaoyu Li, Zhongbao Xin
  • Journal: Remote Sensing
  • Year: 2024