Vision is the complex process of deriving meaning from what is seen. The fields of computer vision and image processing have tried to automate tasks that the human visual system can do, with the aim of gaining a high-level understanding of images and videos. Computer vision algorithms have been successfully applied to a large number of real-world problems ranging from remote sensing to medical image analysis, video surveillance, human-robot interaction, and computer-aided design. In turn, evolutionary computation methods have been shown to be more efficient than classical optimisation approaches for discontinuous, non-differentiable, multimodal, and noisy problems. They have also demonstrated their ability as robust approaches to cope with the fundamental steps of the computer vision and image processing pipeline (e.g. restoration, segmentation, registration, or tracking). As a result of the convergence of the computer vision and evolutionary computation research fields, many research activities, including special sessions, have arisen in the last two decades.
The proposed special session aims to bring together theories and applications of evolutionary computation techniques to computer vision and image processing problems. In this sense, this special session aims to be a meeting place for researchers in the fields of computer vision and/or evolutionary computation, with the aim of enriching both disciplines by means of the hybridisation of state-of-the-art approaches from those domains. We would like to invite researchers to submit contributions on the topic from all viewpoints, including theoretical issues, algorithms, systems, and applications.
This special session will include theories and applications of all evolutionary computation techniques to various computer vision and image processing problems Topics of interest include, but are not limited to:
Please follow the IEEE CEC 2025 Submission Website (https://www.cec2025.org/index/page.html?id=1298) to prepare and submit the paper. Special session papers are treated the same as regular conference papers. All papers accepted and presented at IEEE WCCI/CEC 2025 will be included in the conference proceedings published by IEEE Explore.
Harith Al-Sahaf
Department of Cybersecurity Engineering, Al-Zahraa University for Women, Karbala, Iraq.
Email:Harith.Al-Sahaf@ecs.vuw.ac.nz
Phone: 04-463 5656; Fax: +64-4-463 5045
Homepage: https://al-sahaf.com/harith/
Ying Bi
School of Electrical and Information Engineering, Zhengzhou University, China. Email: yingbi@zzu.edu.cn Homepage: https://yingbi92.github.io/homepage/
Pablo Mesejo
Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada (UGR), Spain Email: pmesejo@go.ugr.es Phone: +34 958241000 Homepage: https://www.ugr.es/~pmesejo/
Harith Al-Sahaf received the B.Sc. degree in computer science from Baghdad University (Iraq), in 2005. He joined the Victoria University of Wellington (VUW), (New Zealand) in July 2007 where he received his MCompSc and PhD degrees in Computer Science in 2010 and 2017, respectively. In October 2016, he has joined the School of Engineering and Computer Science, VUW as a Post-doctoral Research Fellow and as a full-time lecturer since September 2018. His current research interests include evolutionary computation, particularly genetic programming, computer vision, pattern recognition, evolutionary cybersecurity, machine learning, feature manipulation including feature detection, selection, extraction and construction, transfer learning, domain adaptation, one-shot learning, and image understanding. He is the chair of the IEEE CIS ETTC Task Force on Evolutionary Computer Vision and Image Processing, a member of the IEEE CIS ETTC Task Force on Evolutionary Computation for Feature Selection and Construction, the IEEE CIS ISATC Task Force on Evolutionary Deep Learning and Applications, and the IEEE CIC ISATC Task Force on Intelligent Systems for Cybersecurity of IoT.
Ying Bi a distinguished professor with the School of Electrical and Information Engineering at Zhengzhou University, China. She was a postdoc research fellow with the School of Engineering and Computer Science at Victoria University of Wellington (VUW), New Zealand. Her research focuses mainly on evolutionary deep learning, data mining, machine learning, computer vision, evolutionary computation, classification, image analysis, feature learning, and transfer learning. She has published an authored book on Genetic Programming for Image Classification, which is the first book in this field. She has also published over 50 papers in fully refereed journals and conferences such as IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, IEEE Computational Intelligence Magazine, Applied Soft Computing, and Information Sciences. She is a member of IEEE, IEEE Computational Intelligence Society (CIS) and the Association for Computing Machinery (ACM). She is the vice-chair of the IEEE Computational Intelligence Society Task Force on Evolutionary Computer Vision and Image Processing and a member of the IEEE Computational Intelligence Society Task Force on Evolutionary Computation for Feature Selection and Construction. She has been serving as an organising committee member of IEEE CEC 2019 and Australasian AI 2018, the workshop chair of IEEE CEC 2024, associated editor of the journal of IEEE Transactions on Evolutionary Computation, IEEE Transactions on Artificial Intelligence, Intelligent Marine Technology and Systems, a guest editor of the journals of Applied Soft Computing, Memetic Computing and Algorithms, the lead organiser of the workshop on evolutionary data mining and machine learning (EDMML) in IEEE ICDM 2023, 2022, 2021, the co-organizer of the special sessions in IEEE CEC 2023, IEEE WCCI/CEC 2022, IEEE SSCI 2023, 2022, 2021, and IDEAL 2021. Dr Bi has been serving as a program committee member of over ten international conferences including IJCAI, GECCO, IEEE CEC, IEEE SSCI, and Australian AI. She is co-chair of the Poster session in IEEE CEC 2019. She is serving as a reviewer of over twenty international journals including IEEE Transactions on Cybernetics, IEEE Transactions on Evolutionary Computation, IEEE Transactions on Neural Networks and Learning Systems, Applied Soft Computing, and Neurocomputing.
Pablo Mesejo is an Associate Professor at the Department of Computer Science and Artificial Intelligence (DECSAI) of the University of Granada (UGR, Spain). His main research topic is the analysis and design of machine learning, computer vision and computational intelligence methods able to solve image analysis problems, mainly related to the biomedical domain. He has tackled numerous challenging problems, e.g. the automatic segmentation of anatomical structures in biomedical images (PhD at University of Parma, Italy, performed as a Marie Curie Early Stage Researcher, 2010-13), the classification of gastrointestinal lesions from endoscopic videos (postdoc at University of Auvergne, France, in a research lab belonging to CNRS, 2013-14), the estimation of biophysical parameters from fMRI signals (postdoc at Inria, France, 2014-16), and the integration of deep learning into probabilistic generative models for visual and audio recognition in human-robot interaction (starting researcher position at Inria, 2016-18). He joined the UGR in April 2018 as a Marie Curie Experienced Researcher. It is worth mentioning that Marie Curie Standard Individual Fellowships are highly competitive research grants that present a 13.10% success rate (in the H2020-MSCA-IF-2016 call). In turn, the UGR is one of the top institutions in computer science and engineering (ranked 1st in Spain and 101-150 in the world according to the Academic Ranking of World Universities 2020). His Marie Curie proposal (Skeleton-ID) specifically dealt with the application of soft computing and computer vision techniques for the comparison of radiographs in forensic identification. He is co-founder, partner and chief AI officer of Panacea Cooperative Research (a newly-created SME, and UGR spin-off, focused on finding intelligent solutions to solve unmet biomedical needs). He is also the vice-chair of the IEEE Computational Intelligence Society (CIS) Task Force on Evolutionary Computer Vision and Image Processing, member of the IEEE CIS Task Force on Evolutionary Deep Learning and Applications, and member of the Andalusian Research Institute on Data Science and Computational Intelligence (DaSCI).
Program Committee (to be confirmed):