603 citations · 1.2k across the 70 of their papers we have counts for
14 papers · 1 filter
Dual-Reference Source-Free Active Domain Adaptation for Nasopharyngeal Carcinoma Tumor Segmentation across Multiple Hospitals
Hongqiu Wang, Jian Chen, Shichen Zhang +6
Nasopharyngeal carcinoma (NPC) is a prevalent and clinically significant malignancy that predominantly impacts the head and neck area. Precise delineation of the Gross Tumor Volume…
Tracking Players in a Badminton Court by Two Cameras
Young-Ching Chou, Shen-Ru Zhang, Bo-Wei Chen +3
This study proposes a simple method for multi-object tracking (MOT) of players in a badminton court. We leverage two off-the-shelf cameras, one on the top of the court and the othe…
Masked Vision-Language Transformers for Scene Text Recognition
Jie Wu, Ying Peng, Shengming Zhang +2
Scene text recognition (STR) enables computers to recognize and read the text in various real-world scenes. Recent STR models benefit from taking linguistic information in addition…
Reconstruction of compressed spectral imaging based on global structure and spectral correlation
Pan Wang, Jie Li, Jieru Chen +2
In this paper, a convolutional sparse coding method based on global structure characteristics and spectral correlation is proposed for the reconstruction of compressive spectral im…
Seeing your sleep stage: cross-modal distillation from EEG to infrared video
Jianan Han, Shaoxing Zhang, Aidong Men +4
It is inevitably crucial to classify sleep stage for the diagnosis of various diseases. However, existing automated diagnosis methods mostly adopt the "gold-standard" lectroencepha…
2-d signature of images and texture classification
Sheng Zhang, Guang Lin, Samy Tindel
We introduce a proper notion of 2-dimensional signature for images. This object is inspired by the so-called rough paths theory, and it captures many essential features of a 2-dime…
DVHN: A Deep Hashing Framework for Large-scale Vehicle Re-identification
Yongbiao Chen, Sheng Zhang, Fangxin Liu +3
In this paper, we make the very first attempt to investigate the integration of deep hash learning with vehicle re-identification. We propose a deep hash-based vehicle re-identific…
Real-time Keypoints Detection for Autonomous Recovery of the Unmanned Ground Vehicle
Jie Li, Sheng Zhang, Kai Han +3
The combination of a small unmanned ground vehicle (UGV) and a large unmanned carrier vehicle allows more flexibility in real applications such as rescue in dangerous scenarios. Th…
TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval
Yongbiao Chen, Sheng Zhang, Fangxin Liu +3
Deep hamming hashing has gained growing popularity in approximate nearest neighbour search for large-scale image retrieval. Until now, the deep hashing for the image retrieval comm…
Driver Behavior Extraction from Videos in Naturalistic Driving Datasets with 3D ConvNets
Hanwen Miao, Shengan Zhang, Carol Flannagan
Naturalistic driving data (NDD) is an important source of information to understand crash causation and human factors and to further develop crash avoidance countermeasures. Videos…
OGNet: Towards a Global Oil and Gas Infrastructure Database using Deep Learning on Remotely Sensed Imagery
Hao Sheng, Jeremy Irvin, Sasankh Munukutla +10
At least a quarter of the warming that the Earth is experiencing today is due to anthropogenic methane emissions. There are multiple satellites in orbit and planned for launch in t…
Learning to Detect Instantaneous Changes with Retrospective Convolution and Static Sample Synthesis
Chao Chen, Sheng Zhang, Cuibing Du
Change detection has been a challenging visual task due to the dynamic nature of real-world scenes. Good performance of existing methods depends largely on prior background images…
FPGA Implementations of 3D-SIMD Processor Architecture for Deep Neural Networks Using Relative Indexed Compressed Sparse Filter Encoding Format and Stacked Filters Stationary Flow
Yuechao Gao, Nianhong Liu, Sheng Zhang
It is a challenging task to deploy computationally and memory intensive State-of-the-art deep neural networks (DNNs) on embedded systems with limited hardware resources and power b…
Stacked Filters Stationary Flow For Hardware-Oriented Acceleration Of Deep Convolutional Neural Networks
Yuechao Gao, Nianhong Liu, Sheng Zhang
To address memory and computation resource limitations for hardware-oriented acceleration of deep convolutional neural networks (CNNs), we present a computation flow, stacked filte…