Quentin Marc Anaba Fotze | Image Processing and Enhancement | Best Paper Award

Dr. Quentin Marc Anaba Fotze | Image Processing and Enhancement | Best Paper Award

Institute for Geological and Mining Research | Cameroon

Dr. Quentin Marc Anaba Fotze is a geophysicist at the Université de Maroua, Cameroon, specializing in applied geophysics, remote sensing, and geospatial analysis for mineral and groundwater exploration. He has authored 9 indexed publications with 33 citations h-index: 3 and contributed to over scientific works, demonstrating strong collaboration across multidisciplinary teams. His research integrates aeromagnetic, gravity, and satellite data to map tectonic structures, mineralization zones, and groundwater potential in Central Africa. He has also contributed to national geological mapping initiatives, supporting resource management, infrastructure development, and sustainable environmental planning in data-scarce regions.

Citation Metrics (Scopus)

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Citations
33

Documents
9

h-index
3

🟦 Citations 🟥 Documents 🟩 h-index

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Featured Publications

Irenilza De Alencar Nääs | Object Detection and Recognition | Women Researcher Award

Prof. Irenilza De Alencar Nääs | Object Detection and Recognition | Women Researcher Award

Professor | Universidade Paulista | Brazil

Prof. Irenilza de Alencar Nääs is a leading researcher at Universidade Paulista, São Paulo, Brazil, specializing in precision livestock farming, agricultural engineering, and AI-driven animal welfare assessment. She has authored over 339 peer-reviewed publications with more than 3,311 citations h-index 32, reflecting strong international impact and extensive collaboration with more than 400 co-authors worldwide. Her recent work integrates thermography, computer vision (YOLOv8), and machine learning to improve broiler welfare, postharvest quality, and occupational health in agri-food systems. Dr. Nääs’s research significantly advances sustainable agriculture and data-driven decision-making for global food security.

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3,311

Documents
339

h-index
32

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Featured Publications


Princípios de conforto térmico na produção animal .

– Ícone Editora.. (1989). Cited By : 251

Infrared thermal image for assessing animal health and welfare.

-Journal of Animal Behaviour and Biometeorology. (2014). Cited By: 143

Impact of lameness on broiler well-being.

– Journal of Applied Poultry Research. (2009). Cited By: 116

Real time computer stress monitoring of piglets using vocalization analysis.

– Computers and Electronics in Agriculture. (2025). Cited By: 108

Tao Chen | Object Detection and Recognition | Research Excellence Award

Dr. Tao Chen | Object Detection and Recognition | Research Excellence Award

Professor | Fudan University | China

Dr. Tao Chen is a leading researcher at Fudan University, specializing in deep learning and computer vision, with a focus on human motion understanding, 3D shape generation, and semantic segmentation. He has contributed to over 249 high-impact publications in top-tier venues including CVPR, NeurIPS, and IEEE Transactions, accumulating more than 6294 citations. His work integrates advanced neural architectures, motion diffusion, and cross-domain adaptation techniques, often in collaboration with international researchers such as G. Yu and W. Liu. Dr. Chen’s research has significant societal impact, advancing intelligent systems for medical imaging, autonomous perception, and interactive 3D applications, bridging fundamental AI research with practical real-world solutions.

Citation Metrics (Google Scholar)

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Citations
6294

Documents
249

h-index
41

🟦 Citations 🟥 Documents 🟩 h-index

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Featured Publications


Executing your commands via motion diffusion in latent space.

– In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . (2023). Cited By : 580

TopFormer: Token pyramid transformer for mobile semantic segmentation.

-In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). (2022). Cited By: 388

b‑DARTS: Beta‑decay regularization for differentiable architecture search.

– In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). (2022). Cited By: 194

LL3DA: Visual interactive instruction tuning for omni‑3D understanding, reasoning, and planning.

– In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). (2024). Cited By: 178

Zeng Gao | Applications of Computer Vision | Research Excellence Award

Dr. Zeng Gao | Applications of Computer Vision | Research Excellence Award

Lecturer | Henan University of Technology | China 

Dr. Zeng Gao is a researcher at Henan University of Technology specializing in machine learning, image processing, and visual tracking. His work focuses on intelligent optimization–driven visual tracking and motion analysis, with influential contributions to abrupt and long-term tracking. He has published over 12 peer-reviewed papers in leading international journals and conferences, including IEEE Access, Expert Systems with Applications, Applied Soft Computing, Digital Signal Processing, and PRCV, accumulating 98 citations. He has participated in two National Natural Science Foundation of China projects and holds three granted invention patents. Dr. Gao actively collaborates with domestic and international institutions, serves as a reviewer for journals such as ACM TOMM and Digital Signal Processing, and contributes to advancing intelligent perception technologies with real-world societal impact.

 

Citation Metrics (Scopus)

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Citations
98

Documents
12

h-index
7

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Featured Publications


Visual tracking with levy flight grasshopper optimization algorithm.

– Pattern Recognition and Computer Vision: Second Chinese Conference, PRCV  (2019). Cited By : 19

Xinrong Hu | Object Detection and Recognition | Women Researcher Award

Prof. Xinrong Hu | Object Detection and Recognition | Women Researcher Award

Dean of Computer Science and Artificial Intelligence | Wuhan Textile University | China

Prof. Xinrong Hu is a distinguished researcher and academic leader in computer vision, natural language processing, virtual reality, and machine learning. She serves as Dean of the School of Computer and Artificial Intelligence at Wuhan Textile University and is a doctoral supervisor, leading an innovative research team at the Hubei Provincial Engineering Technology Research Center for Garment Informatization. She holds a Ph.D. and has extensive experience in guiding research projects, including over 30 funded initiatives, some with national and international significance. Her research interests focus on advancing artificial intelligence applications in real-world scenarios, combining theoretical innovation with practical solutions. She has authored more than 100 academic papers, edited six textbooks, translated a book, and holds 26 invention patents, demonstrating her strong research skills and contribution to knowledge dissemination. Prof. Hu has been recognized with multiple awards and honors, including provincial and ministerial-level scientific research awards, teaching achievement awards, and prestigious titles such as Hubei Provincial Distinguished Teacher and recipient of the Special Government Allowance from the State Council. Her professional engagement includes leadership in academic communities, mentorship of young researchers, and active participation in advancing the field of AI through both education and research initiatives. Her comprehensive expertise, innovative contributions, and dedication to fostering academic excellence make her a leading figure in her field. Her research impact is reflected in 1,044 citations, 209 documents, and an h-index of 16.

Profiles: Scopus | ResearchGate 

Featured Publications

  1. Hu, X., et al. (2025). CDPMF-DDA: Contrastive deep probabilistic matrix factorization for drug-disease association prediction. BMC Bioinformatics.

  2. Hu, X., et al. (2025). Source-free cross-modality medical image synthesis with diffusion priors. Journal of King Saud University – Computer and Information Sciences.

  3. Hu, X., et al. (2025). TADUFMA: Transformer-based adaptive denoising and unified feature modeling for multi-condition anomaly detection in computerized flat knitting machines. Measurement Science and Technology.

  4. Hu, X., et al. (2025). ViT-BF: Vision transformer with border-aware features for visual tracking. Visual Computer.

  5. Hu, X., et al. (2025). Adaptive debiasing learning for drug repositioning. Journal of Biomedical Informatics.

Fatma Zahra Sayadi | Deep Learning | Best Innovation Award

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.

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.