Applications of Nonlinear Diffusion Models and Deep Learning in Computer Vision
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 15 November 2026 | Viewed by 454
Editor
Interests: static and video image processing and analysis; machine and deep learning; computer vision; PDE models; biometrics; numerical analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The deep neural networks and nonlinear diffusion equations have been applied succesfully in various image and video processing and analysis domains in the last decades. These research fields, which include static and video image filtering, inpainting, segmentation, compression, decomposition, registration, feature extraction, classification and motion estimation, have important computer vision and artificial intelligence application areas, such as image and video recognition, scene understanding, content-based image indexing and retrieval, object detection, recognition and tracking, activity recognition, medical imaging and robotic vision.
The scope of this Special Issue is to diseminate advanced and novel techniques in these computer vision domains, which use nonlinear diffusion schemes, deep learning (DL) methods or combined approaches based on partial differential equations (PDE) and convolutional neural networks (CNN), and to bring together valuable researchers working in these fields.
We encourage you to submit for this Special Issue high-quality articles that describe original research achievements in computer vision topics, which include but are not limited to, the following:
- Image preprocessing for computer vision using deep learning and PDE models
- Multi-scale image analysis combining diffusion-based scale-spaces to CNN-based features
- Static and video image segmentation based on nonlinear diffusion and deep learning models
- Nonlinear PDE-based CNN architectures for computer vision
- Deep content-based image indexing and retrieval (CBIR)
- CNN-based image and object recognition
- Object detection and tracking using PDE-based active contours and deep neural networks
- Deep human action recognition
- Medical image diagnosis combining deep learning to nonlinear diffusion models
Prof. Dr. Tudor Barbu
Guest Editor
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Keywords
- deep learning
- nonlinear diffusion
- image and video analysis
- indexing and retrieval
- image and video segmentation
- image classification
- object detection, recognition and tracking
- action recognition
- medical imaging
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