5 papers
Displacement Preserving Relational Distillation for Robust Medical Segmentation
Zhicheng Ding, Xinyu Chu, Jung Im Choi +5
Accurate 3D medical segmentation is limited by anatomical variability and high computational costs. While knowledge distillation (KD) offers a route for model compression, conventi…
Learnable Instance Attention Filtering for Adaptive Detector Distillation
Chen Liu, Qizhen Lan, Zhicheng Ding +2
As deep vision models grow increasingly complex to achieve higher performance, deployment efficiency has become a critical concern. Knowledge distillation (KD) mitigates this issue…
Topology-Guided Knowledge Distillation for Efficient Point Cloud Processing
Luu Tung Hai, Thinh D. Le, Zhicheng Ding +2
Point cloud processing has gained significant attention due to its critical role in applications such as autonomous driving and 3D object recognition. However, deploying high-perfo…
Improved AdaBoost for Virtual Reality Experience Prediction Based on Long Short-Term Memory Network
Wenhan Fan, Zhicheng Ding, Ruixin Huang +2
A classification prediction algorithm based on Long Short-Term Memory Network (LSTM) improved AdaBoost is used to predict virtual reality (VR) user experience. The dataset is rando…
Optimizing Contrail Detection: A Deep Learning Approach with EfficientNet-b4 Encoding
Qunwei Lin, Qian Leng, Zhicheng Ding +2
In the pursuit of environmental sustainability, the aviation industry faces the challenge of minimizing its ecological footprint. Among the key solutions is contrail avoidance, tar…