Guest Editors
Dr. Sultan Daud Khan, National University of Technology, Pakistan
Dr. Saleh Basalamah, Al-Qura University, Saudi Arabia
Dr. Farhan Riaz, University of Lincoln, UK
Summary
Semantic segmentation is a fundamental task in computer vision, which aims to partition an image into different regions corresponding to different semantic concepts. It has a wide range of applications such as object recognition, scene understanding, and autonomous driving. With the recent advancements in deep learning, particularly the success of convolutional neural networks (CNNs), semantic segmentation has seen significant progress in terms of accuracy and efficiency. However, there are still many challenges that need to be addressed in order to improve its performance in real-world scenarios.
Keywords
- Novel deep learning architectures for semantic segmentation
- Multi-modal semantic segmentation
- Weakly supervised and unsupervised semantic segmentation
- Real-time semantic segmentation
- Semantic segmentation for autonomous driving
- Transfer learning for semantic segmentation
- Domain adaptation for semantic segmentation
- Evaluation metrics for semantic segmentation
- Applications of semantic segmentation in various domains
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