Recent Advances in Deep Learning Algorithms for Computer Vision and Image Analysis
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 4
Special Issue Editor
Special Issue Information
Dear Colleagues,
Computer vision has become a key area of modern technology, driving innovation in automation, intelligent systems, and human–machine interaction to address a wide range of real-world challenges. Powered by deep learning, it enables machines to interpret and understand visual information, opening new horizons for science, engineering, and society.
This Special Issue aims to bring together cutting-edge contributions at the intersection of engineering, computer science, and related disciplines, highlighting innovative methods, architectures, and applications. The topics of interest include, but are not limited to, the use of deep neural networks, convolutional architectures, transformer-based vision models, image segmentation, object detection, image enhancement, 3D reconstruction, multimodal data fusion, and explainable AI in vision systems. We particularly welcome work addressing multidisciplinary applications, such as robotics, industrial automation, biomedical engineering, smart cities, and intelligent transportation. We also encourage the submission of studies on how computer vision and image analysis are transforming the creation, validation, and operation of virtual models and realistic simulations in the context of digital twins across multiple domains.Submissions should present novel methodologies, theoretical advances, or significant practical implementations. Both experimental and theoretical studies are encouraged, as well as interdisciplinary research combining knowledge from various engineering fields.
Prof. Dr. Marcelo Rudek
Guest Editor
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Keywords
- deep neural networks
- convolutional architectures
- transformer-based vision models
- object detection and tracking
- image segmentation
- image enhancement
- 3D reconstruction
- multimodal data fusion
- explainable AI in vision systems
- vision in virtual simulations and digital twins
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