- Edge AI and embedded vision systems
- Efficient neural network architectures for edge devices
- Model compression, quantization, and pruning techniques
- On-device training and continual learning
- Energy-efficient AI algorithms
- Computer vision for mobile and autonomous systems
- Sensor fusion and multimodal processing on edge hardware
- Applications in healthcare, agriculture, environmental science, and manufacturing
- Challenges in deployment on drones, IoT devices, and mobile robots
- Benchmarking and evaluation methodologies for edge AI systems
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ICTCon2025