most citedAn Unsupervised Domain Adaptation Model based on Dual-module Adversarial Training

29 citations · 38 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20231 cited

Aphid Cluster Recognition and Detection in the Wild Using Deep Learning Models

Tianxiao Zhang, Kaidong Li, Xiangyu Chen +7

Aphid infestation poses a significant threat to crop production, rural communities, and global food security. While chemical pest control is crucial for maximizing yields, applying…

cs.CV20232 cited

A New Dataset and Comparative Study for Aphid Cluster Detection

Tianxiao Zhang, Kaidong Li, Xiangyu Chen +7

Aphids are one of the main threats to crops, rural families, and global food security. Chemical pest control is a necessary component of crop production for maximizing yields, howe…

cs.CV2023

Gender, Smoking History and Age Prediction from Laryngeal Images

Tianxiao Zhang, Andrés M. Bur, Shannon Kraft +5

Flexible laryngoscopy is commonly performed by otolaryngologists to detect laryngeal diseases and to recognize potentially malignant lesions. Recently, researchers have introduced…

cs.LG202129 cited

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…

cs.CV20216 cited

Miti-DETR: Object Detection based on Transformers with Mitigatory Self-Attention Convergence

Wenchi Ma, Tianxiao Zhang, Guanghui Wang

Object Detection with Transformers (DETR) and related works reach or even surpass the highly-optimized Faster-RCNN baseline with self-attention network architectures. Inspired by t…