ArtInHCI-DL'23
ArtInHCI Deep Learning Session (ArtInHCI-DL'23) is conducted under the International Conference on Artificial Intelligence and Human-Computer Interaction, held during October 27-29, 2023 in Wuhan, China.
Deep learning has achieved great success in fields such as computer vision and natural language processing, and are being applied in application scenarios such as autonomous driving, intelligent finance, and smart healthcare.
The session aims to bring together researchers and developers in relevant fields from academia and industry to discuss and showcase the latest research and innovations in theory, algorithms, and system technologies, and to discuss future research directions. Through this session, we hope to promote the development of deep learning-based artificial intelligence technologies in various fields. We encourage research groups to submit relevant papers on this topic, including new theoretical methods, innovative applications, and system prototypes.
Topics include but are not limited to:
- Deep learning architectures
- Efficient deep learning methods
- Neural networks (ANN, CNN, RNN, etc.)
- Computer vision
- Natural language processing
- Few-shot/zero-shot learning
- Visual reasoning
- Clustering, classification, and regression.
ArtInHCI-DL'23 Call for Paper Flyer
ArtInHCI-DL'23 Session Chair
Institute of Artificial Intelligence
Beihang University, China
Areas of Expertise: large-scale machine learning, efficient methods, computer vision, natural language processing, pattern recognition and artificial intelligence
Brief Introduction: Jinyang Guo received the PhD degree from the University of Sydney in 2022 and the BE (Hons1) degree from the University of New South Wales in 2017. He is currently an Assistant Professor with the Institute of Artificial Intelligence, Beihang University. His research interests include efficient machine/deep learning methods and its applications on computer vision, natural language processing. His works have been published on top-tier journals and conferences (e.g., T-IP, CVPR and AAAI). He serves as the reviewers/program committee members for T-PAMI, IJCV, CVPR, ICCV, etc.