2 citations · 4 across the 4 of their papers we have counts for
4 papers
Transformer-based Selective Super-Resolution for Efficient Image Refinement
Tianyi Zhang, Kishore Kasichainula, Yaoxin Zhuo +3
Conventional super-resolution methods suffer from two drawbacks: substantial computational cost in upscaling an entire large image, and the introduction of extraneous or potentiall…
Patch-based Selection and Refinement for Early Object Detection
Tianyi Zhang, Kishore Kasichainula, Yaoxin Zhuo +3
Early object detection (OD) is a crucial task for the safety of many dynamic systems. Current OD algorithms have limited success for small objects at a long distance. To improve th…
FedNS: Improving Federated Learning for collaborative image classification on mobile clients
Yaoxin Zhuo, Baoxin Li
Federated Learning (FL) is a paradigm that aims to support loosely connected clients in learning a global model collaboratively with the help of a centralized server. The most popu…
Weakly Supervised Deep Image Hashing through Tag Embeddings
Vijetha Gattupalli, Yaoxin Zhuo, Baoxin Li
Many approaches to semantic image hashing have been formulated as supervised learning problems that utilize images and label information to learn the binary hash codes. However, la…