427 citations · 3.3k across the 77 of their papers we have counts for
11 papers · 1 filter
Temporal Modeling Matters: A Novel Temporal Emotional Modeling Approach for Speech Emotion Recognition
Jiaxin Ye, Xin-cheng Wen, Yujie Wei +3
Speech emotion recognition (SER) plays a vital role in improving the interactions between humans and machines by inferring human emotion and affective states from speech signals. W…
When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework and A New Benchmark
Zhizhong Huang, Junping Zhang, Hongming Shan
To minimize the impact of age variation on face recognition, age-invariant face recognition (AIFR) extracts identity-related discriminative features by minimizing the correlation b…
Motion Matters: A Novel Motion Modeling For Cross-View Gait Feature Learning
Jingqi Li, Jiaqi Gao, Yuzhen Zhang +2
As a unique biometric that can be perceived at a distance, gait has broad applications in person authentication, social security, and so on. Existing gait recognition methods suffe…
Quad-Net: Quad-domain Network for CT Metal Artifact Reduction
Zilong Li, Qi Gao, Yaping Wu +5
Metal implants and other high-density objects in patients introduce severe streaking artifacts in CT images, compromising image quality and diagnostic performance. Although various…
SAN-Net: Learning Generalization to Unseen Sites for Stroke Lesion Segmentation with Self-Adaptive Normalization
Weiyi Yu, Zhizhong Huang, Junping Zhang +1
There are considerable interests in automatic stroke lesion segmentation on magnetic resonance (MR) images in the medical imaging field, as stroke is an important cerebrovascular d…
Forget Less, Count Better: A Domain-Incremental Self-Distillation Learning Benchmark for Lifelong Crowd Counting
Jiaqi Gao, Jingqi Li, Hongming Shan +4
Crowd counting has important applications in public safety and pandemic control. A robust and practical crowd counting system has to be capable of continuously learning with the ne…
Convolutional Neural Network to Restore Low-Dose Digital Breast Tomosynthesis Projections in a Variance Stabilization Domain
Rodrigo de Barros Vimieiro, Chuang Niu, Hongming Shan +3
Digital breast tomosynthesis (DBT) exams should utilize the lowest possible radiation dose while maintaining sufficiently good image quality for accurate medical diagnosis. In this…
Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels
Yiming Lei, Haiping Zhu, Junping Zhang +1
The performance of medical image classification has been enhanced by deep convolutional neural networks (CNNs), which are typically trained with cross-entropy (CE) loss. However, w…
Physics-/Model-Based and Data-Driven Methods for Low-Dose Computed Tomography: A survey
Wenjun Xia, Hongming Shan, Ge Wang +1
Since 2016, deep learning (DL) has advanced tomographic imaging with remarkable successes, especially in low-dose computed tomography (LDCT) imaging. Despite being driven by big da…
OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines
Aaron Babier, Rafid Mahmood, Binghao Zhang +56
We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients w…
Deep Rank-Consistent Pyramid Model for Enhanced Crowd Counting
Jiaqi Gao, Zhizhong Huang, Yiming Lei +4
Most conventional crowd counting methods utilize a fully-supervised learning framework to establish a mapping between scene images and crowd density maps. They usually rely on a la…