Visual Object Detection in Intelligent Transport System
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 12
Special Issue Editor
Special Issue Information
Dear Colleagues,
This Special Issue focuses on advances in visual object detection for road environments, including the detection and tracking of vehicles, pedestrians, cyclists, traffic signs, and road hazards. We welcome contributions that address core challenges in ITS such as operation under adverse weather and lighting, occlusions, long-tail and open-set classes, and cross-domain generalization across cities, cameras, and platforms. Topics include deep learning architectures (e.g., transformer-based and multi-scale detectors), 3D detection, multi-object tracking, and integration with segmentation and scene understanding. We encourage work on multi-modal sensing and fusion (camera, LiDAR, radar), data-efficient learning (self-/semi-supervised, synthetic data), model compression and quantization for real-time edge deployment, uncertainty estimation, calibration, robustness, explainability, and safety. System-oriented submissions on multi-camera networks, V2X, edge–cloud coordination, and standardized evaluation protocols, datasets, and benchmarks are also within the scope.
The Special Issue invites original research, comprehensive reviews, datasets/benchmarks, hardware–software co-design studies, reproducibility reports, and field trials demonstrating real-world impact in traffic monitoring, ADAS/autonomous driving, and smart infrastructure.
Dr. Andreas Specker
Guest Editor
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Keywords
- visual object detection
- intelligent transport systems
- multi-modal sensor fusion
- real-time edge inference
- adverse weather robustness
- domain adaptation and generalization
- multi-object tracking
- 3D detection
- datasets, benchmarks, and evaluation metrics
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