Special Session 2

 

Special Session 2: Lightweight Deep Learning Models and Applications

Organizer: Prof. Feifei Tang, Chongqing Jiaotong University
                   Dr. Tao Zhou, Deakin University
                   Dr. Yit Hong Choo, Deakin University
                   Xinjie Deng, Deakin University

 

About the session


This special session is dedicated to the design and development of lightweight deep learning (DL) models and their practical applications. These DL models are able to achieve efficiency and ensure performance in undertaking complex tasks effectively while using minimal computational power. The emphasis on lightweight models is critical for enabling real-time data processing, as they can significantly minimise processing delays and enhance the speed and responsiveness in various real-time applications. They are also useful for deployment in resource-constrained devices like smartphones, IoT (Internet-of-Things) devices, and edge computing platforms.
In this special session, we solicit papers that study the fundamental theories and principles underpinning the design and development of lightweight DL models for efficient and effective computation. Papers that demonstrate how lightweight DL models are applied to solve real-world problems efficiently are also welcome. The scope of this special session includes, but is not limited to, the following topics:
• Optimisation techniques for reduced computational complexity of DL models
• Deployment strategies of DL models on resource-constrained devices
• Real-time data processing of DL models
• Methods for minimising processing delays in DL models
• Techniques for on-device data analytics with DL models
• Privacy and security enhancements of DL models through edge computing.
• Applications of lightweight DL models in various domains, such as:
o Internet of Things (IoT)
o Autonomous systems and robotics
o Smart city infrastructures
o Intelligent Transportation

Keywords
• Artificial intelligence
• Machine learning
• Deep learning
• Supervised learning
• Reinforcement learning
• Domain adaptation
• Scalability
• Optimisation
• Computational intelligence
• Real-world problems
• Lightweight models
• Intelligent transportation
• Remote sensing

Submission Guidelines

Please submit your manuscript via Electronic Submission System (account is needed). (Please choose the special number when you make the submission.)

Important Dates

    ◆ Submission of Full Papers: Apr. 25, 2025
    ◆ Notification of Review Result of Papers from Special Sessions: May. 10, 2025