29 citations · 36 across the 6 of their papers we have counts for
6 papers
An Unsupervised Domain Adaptation Model based on Dual-module Adversarial Training
Yiju Yang, Tianxiao Zhang, Guanyu Li +2
In this paper, we propose a dual-module network architecture that employs a domain discriminative feature module to encourage the domain invariant feature module to learn more doma…
Audio-Visual Transformer Based Crowd Counting
Usman Sajid, Xiangyu Chen, Hasan Sajid +2
Crowd estimation is a very challenging problem. The most recent study tries to exploit auditory information to aid the visual models, however, the performance is limited due to the…
Multiple Classifiers Based Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
Yiju Yang, Taejoon Kim, Guanghui Wang
Adversarial training based on the maximum classifier discrepancy between two classifier structures has achieved great success in unsupervised domain adaptation tasks for image clas…
Dual Optimization for Kolmogorov Model Learning Using Enhanced Gradient Descent
Qiyou Duan, Hadi Ghauch, Taejoon Kim
Data representation techniques have made a substantial contribution to advancing data processing and machine learning (ML). Improving predictive power was the focus of previous rep…
Parallel Scale-wise Attention Network for Effective Scene Text Recognition
Usman Sajid, Michael Chow, Jin Zhang +2
The paper proposes a new text recognition network for scene-text images. Many state-of-the-art methods employ the attention mechanism either in the text encoder or decoder for the…
A Hybrid Cache Architecture for Meeting Per-Tenant Performance Goals in a Private Cloud
Taejoon Kim, Yu Gu, Jinoh Kim
The in-memory cache system is an important component in a cloud for the data access performance. As the tenants may have different performance goals for data access depending on th…