1 citations · 1 across the 5 of their papers we have counts for
5 papers
ShortcutBreaker: Low-Rank Noisy Bottleneck and Frequency Filtering Block for Multi-Class Unsupervised Anomaly Detection
Peng Tang, Xiaobin Hu, Tingcheng Li +3
Multi-class unsupervised anomaly detection (MUAD) has garnered growing research interest, as it seeks to develop a unified model for anomaly detection across multiple classes, i.e.…
Pay Less On Clinical Images: Asymmetric Multi-Modal Fusion Method For Efficient Multi-Label Skin Lesion Classification
Peng Tang, Tobias Lasser
Existing multi-modal approaches primarily focus on enhancing multi-label skin lesion classification performance through advanced fusion modules, often neglecting the associated ris…
Single-Shared Network with Prior-Inspired Loss for Parameter-Efficient Multi-Modal Imaging Skin Lesion Classification
Peng Tang, Tobias Lasser
In this study, we introduce a multi-modal approach that efficiently integrates multi-scale clinical and dermoscopy features within a single network, thereby substantially reducing…
Joint-Individual Fusion Structure with Fusion Attention Module for Multi-Modal Skin Cancer Classification
Peng Tang, Xintong Yan, Yang Nan +3
Most convolutional neural network (CNN) based methods for skin cancer classification obtain their results using only dermatological images. Although good classification results hav…
SR-RKAC: Improving Single Image Defocus Deblurring
Peng Tang, Zhiqiang Xu, Pengfei Wei +5
We propose an efficient deep learning method for single image defocus deblurring (SIDD) by further exploring inverse kernel properties. Although the current inverse kernel method,…