ICMLC 2027 will be held in Shenzhen, China on February 26-March 01, 2027. The ICMLC 2027 organizing committees invite you to submit the papers to special session. Each special session will be arranged for around 2 hours on Feb. 27 or 28's afternoon. Now the information on special session as following:

Topic: Efficient and Lightweight Deep Learning for Edge and Industrial Applications

Organizers | 组织者

 

The rapid deployment of deep learning across industrial automation, robotics, IoT, and embedded systems has exposed a persistent gap between the accuracy of state-of-the-art models and the strict memory, latency, and power budgets of edge and industrial hardware. Cloud-dependent inference is often impractical in factories, infrastructure inspection, and remote monitoring settings, where connectivity is limited and real-time decisions are safety-critical. This Special Session invites original research on efficient and lightweight deep learning methods designed to close that gap, including model compression, quantization, pruning, knowledge distillation, and compact architecture design for deployment on edge devices, embedded processors, and industrial systems. We particularly welcome contributions addressing lightweight anomaly and fault detection, real-time visual inspection, energy-aware training and inference, and neural architecture search under resource constraints, alongside studies that evaluate the trade-offs between accuracy, robustness, interpretability, and computational cost. The session aims to bring together researchers and practitioners from academia and industry to share methodological advances, benchmark results, and deployment experience, and to foster discussion on open challenges in building deep learning systems that are efficient enough to run reliably on constrained industrial and edge hardware while remaining accurate and trustworthy in practice.

The scopes as following:
• Lightweight and compact neural network architectures for edge devices
• Model quantization, pruning, and knowledge distillation
• Efficient and lightweight anomaly and fault detection for industrial systems
• Real-time inference on embedded, mobile, and edge processors
• Neural architecture search under resource and energy constraints
• Edge AI for IoT, robotics, and industrial automation

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Welcome to submit more proposal on ICMLC 2027 special session, please download:
 Proposals Submission Guidelines.

Learn more details or submit the proposal, please contact us:
Ms. Doris Ge
Email: icmlc@vip.126.com
Tel: +86-13709044746