Computer Vision

Depth Shrink: Empowering Hardware-Friendly Shallow Neural Networks
Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation
SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training
AlphaNet: Improved Training of Supernets with Alpha-Divergence
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling
KeepAugment: A Simple Information-Preserving Data Augmentation Approach
Co-exploration of neural architectures and heterogeneous asic accelerator designs targeting multiple tasks
Federated Learning with Non-IID Data
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