Image and Signal Processing Techniques and Applications, 2nd Edition
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 January 2027 | Viewed by 445
Editors
Interests: geometric-invariant deep learning; remote sensing image analysis; affective computing
Special Issues, Collections and Topics in MDPI journals
Interests: image sparse representation and compression sensing theory; image denoising and segmentation; SAR image denoising and terrain classification; SAR target detection and recogn
Special Issues, Collections and Topics in MDPI journals
Interests: image registration; domain adaptation; multimodal learning; and intelligent signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Image and signal processing techniques have made remarkable progress over the past two decades and have been applied in various scenarios. The core step in image and signal analysis is feature extraction, which can be categorized into two primary approaches: knowledge-driven handcrafted features and data-driven deep learning methods. The former excels in feature interpretability, computational efficiency, and performance predictability, while the latter demonstrates significant advantages in feature generalization, high-level semantic representation, and multi-modal/heterogeneous data modeling and has achieved remarkable results in large-scale datasets, supporting various image and signal analysis tasks. Recently, researchers have begun to explore knowledge–data collaborative approaches for feature extraction in image and signal processing, focusing on algorithm reliability, feature interpretability, and model parameter lightweighting. Moreover, the emergence of large language models and vision–language models has further advanced research in multi-modal heterogeneous data feature alignment and fusion for image and signal processing. This Special Issue invites authors to submit their latest research on image and signal processing methods, particularly those related to feature extraction (including both handcrafted and deep learning-based methods). Possible contributions include, but are not limited to, the following: robust/invariant feature extraction, feature interpretability, lightweight deep learning models, multi-modal feature alignment and fusion, and other related research in the fields of computer vision, pattern recognition, and signal processing. Additionally, application-oriented studies in areas such as remote sensing, affective computing, and industrial production are highly welcome.
Dr. Hanlin Mo
Dr. Shuang Wang
Dr. Yu Gu
Guest Editors
Manuscript Submission Information
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Keywords
- computer vision
- signal processing
- feature extraction
- handcrafted features
- deep neural networks
- feature reliability and interpretability
- lightweight deep learning
- multi-modal feature alignment and fusion
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Related Special Issue
- Image and Signal Processing Techniques and Applications in Electronics (5 articles)
