Explanipedia

Efficient Data-Driven Modeling of Core Loss in Magnetic Materials for Power Electronics Systems Open

Junqi He, Siyang Li, Hao Sheng, Rui Gao, Ying Luo , et al. · 2025

The accurate modeling and prediction of magnetic core losses are of great significance in the design of power electronic systems. Although traditional empirical equations (such as Steinmetz equation and its improved forms) are easy to calc…

Double Check My Desired Return: Transformer with Target Alignment for Offline Reinforcement Learning Open

Y. P. Pei, Hongming Zhang, Chao Gao, Martin Müller, Mengxiao Zhu , et al. · 2025

Offline reinforcement learning (RL) has achieved significant advances in domains such as robotic control, autonomous driving, and medical decision-making. Most existing methods primarily focus on training policies that maximize cumulative …

Multi-Agent-Supported Tracking Based on Hidden Markov Model with Weighted Entropy Open

Hao Sheng, Haoyu Gao, Shuai Wang, Da Yang, Dazhi Yang , et al. · 2025

Multi-object tracking (MOT) has witnessed significant advancements in recent years, yet it remains challenged by complex uncertainties arising from pedestrian movement patterns. To address this, we present a unified framework that explicit…

YED-Net: Yoga Exercise Dynamics Monitoring with YOLOv11-ECA-Enhanced Detection and DeepSORT Tracking Open

Youyu Zhou, Dong Shu, Hao Sheng, Wei Ke · 2025

Against the backdrop of the deep integration of national fitness and sports science, this study addresses the lack of standardized movement assessment in yoga training by proposing an intelligent analysis system that integrates an improved…

Occlusion-Robust Multi-Target Tracking and Segmentation Framework with Mask Enhancement Open

Hao Sheng, Defa Zhang, Dazhi Yang, Da Yang, Liu Xi , et al. · 2025

Multi-object tracking stands as one of the most prominent domains in Computer Vision and has significant research value and practical importance. However, due to the complexity of scenarios in the real world, especially in crowded environm…

Wavelet-Based Multi-Level Information Compensation Learning for Visible-Infrared Person Re-Identification Open

Hongqi Fan, Yanbing Chen, Yibo Chen, Zhixin Tie, Hao Sheng , et al. · 2025

Advances in Light Field Spatial Super-Resolution: A Comprehensive Literature Survey Open

Wenqi Lyu, Hao Sheng, Wei Ke, Xiao Ma · 2025

Super-resolution reconstruction of light field images has recently become a central focus in the fields of computational photography and computer vision. We present a systematic review of 17 mainstream light field spatial super-resolution …

Improved Localization and Recognition of Handwritten Digits on MNIST Dataset with ConvGRU Open

Yalin Wen, Wei Ke, Hao Sheng · 2024

Video location prediction for handwritten digits presents unique challenges in computer vision due to the complex spatiotemporal dependencies and the need to maintain digit legibility across predicted frames, while existing deep learning-b…

EVA-S3PC: Efficient, Verifiable, Accurate Secure Matrix Multiplication Protocol Assembly and Its Application in Regression Open

S. Andrew Peng, Tianrui Liu, Terence Tao, D.X. Zhao, Hao Sheng , et al. · 2024

Efficient multi-party secure matrix multiplication is crucial for privacy-preserving machine learning, but existing mixed-protocol frameworks often face challenges in balancing security, efficiency, and accuracy. This paper presents an eff…

Two-Stage Locating and Capacity Optimization Model for the Ultra-High-Voltage DC Receiving End Considering Carbon Emission Trading and Renewable Energy Time-Series Output Reconstruction Open

Lang Zhao, Zhidong Wang, Hao Sheng, Yizheng Li, Tianqi Zhang , et al. · 2024

With the load center’s continuous expansion and development of the AC power grid’s scale and construction, the recipient grid under the multi-feed DC environment is facing severe challenges of DC commutation failure and bipolar blocking du…

End-to-end multimodal deep learning for real-time decoding of months-long neural activity from the same cells Open

Yichun He, Arnau Marin‐Llobet, Hao Sheng, Liu Ren, Jia Liu · 2024

Long-term, stable, and real-time decoding of behavior-dependent neural dynamics from the same cells is critical for brain-computer interfaces (BCIs) and for understanding neural evolution during learning, and memory, and disease progressio…

RANDnet: Vehicle Re-Identification with Relation Attention and Nuance–Disparity Masks Open

Yang Huang, Hao Sheng, Wei Ke · 2024

Vehicle re-identification (vehicle ReID) is designed to recognize all instances of a specific vehicle across various camera viewpoints, facing significant challenges such as high similarity among different vehicles from the same viewpoint …

Dynamic Downsampling Algorithm for 3D Point Cloud Map Based on Voxel Filtering Open

Wenqi Lyu, Wei Ke, Hao Sheng, Xiao Ma, Huayun Zhang · 2024

In response to the challenge of handling large-scale 3D point cloud data, downsampling is a common approach, yet it often leads to the problem of feature loss. We present a dynamic downsampling algorithm for 3D point cloud maps based on an…

Transformer-Based Semantic Entity Recognition for Chinese Medical Inspection Reports Open

Honglin Wan, Hao Sheng, Xiangzhi Kong, Qiuyue Li, Tong Zhang · 2024

With the rapid development of the Internet, the application of artificial intelligence in the medical field has become a focus of attention. At present, understanding the Chinses medical inspection report (CMIR) is of great significance fo…

Camouflaged Object Detection Based on Deep Learning with Attention-Guided Edge Detection and Multi-Scale Context Fusion Open

Yalin Wen, Wei Ke, Hao Sheng · 2024

In nature, objects that use camouflage have features like colors and textures that closely resemble their background. This creates visual illusions that help them hide and protect themselves from predators. This similarity also makes the t…

MSIE-Net: Associative Entity-Based Multi-Stage Network for Structured Information Extraction from Reports Open

Qiuyue Li, Hao Sheng, Mingxue Sheng, Honglin Wan · 2024

Efficient document recognition and sharing remain challenges in the healthcare, insurance, and finance sectors. One solution to this problem has been the use of deep learning techniques to automatically extract structured information from …

A survey for light field super-resolution Open

Mingyuan Zhao, Hao Sheng, Da Yang, Sizhe Wang, Ruixuan Cong , et al. · 2024

Compared to 2D imaging data, the 4D light field (LF) data retains richer scene’s structure information, which can significantly improve the computer’s perception capability, including depth estimation, semantic segmentation, and LF renderi…

Light field depth estimation: A comprehensive survey from principles to future Open

Tun Wang, Hao Sheng, Rongshan Chen, Da Yang, Zhenglong Cui , et al. · 2023

Light Field (LF) depth estimation is an important research direction in the area of computer vision and computational photography, which aims to infer the depth information of different objects in three-dimensional scenes by capturing LF d…

Parallel Dense Video Caption Generation with Multi-Modal Features Open

Xuefei Huang, Ka‐Hou Chan, Wei Ke, Hao Sheng · 2023

The task of dense video captioning is to generate detailed natural-language descriptions for an original video, which requires deep analysis and mining of semantic captions to identify events in the video. Existing methods typically follow…

Light field super-resolution using complementary-view feature attention Open

Wei Zhang, Wei Ke, Da Yang, Hao Sheng, Zhang Xiong · 2023

Light field (LF) cameras record multiple perspectives by a sparse sampling of real scenes, and these perspectives provide complementary information. This information is beneficial to LF super-resolution (LFSR). Compared with traditional si…

Take Your Model Further: A General Post-refinement Network for Light Field Disparity Estimation via BadPix Correction Open

Rongshan Chen, Hao Sheng, Da Yang, Sizhe Wang, Zhenglong Cui , et al. · 2023

Most existing light field (LF) disparity estimation algorithms focus on handling occlusion, texture-less or other areas that harm LF structure to improve accuracy, while ignoring other potential modeling ideas. In this paper, we propose a …

CoGAN: Cooperatively trained conditional and unconditional GAN for person image generation Open

Yang Liu, Hao Sheng, Shuai Wang, Yubin Wu, Zhang Xiong · 2023

Person image generation aims to synthesize realistic person images that follow the same distribution as the given dataset. Previous attempts can be generally categorized into two classes: conditional GAN and unconditional GAN. The former u…

Fusion of Multi-Modal Features to Enhance Dense Video Caption Open

Xuefei Huang, Ka‐Hou Chan, Weifan Wu, Hao Sheng, Wei Ke · 2023

Dense video caption is a task that aims to help computers analyze the content of a video by generating abstract captions for a sequence of video frames. However, most of the existing methods only use visual features in the video and ignore…

Distributed Truss Computation in Dynamic Graphs Open

Ziwei Mo, Qi Luo, Dongxiao Yu, Hao Sheng, Jiguo Yu , et al. · 2023

Large-scale graphs usually exhibit global sparsity with local cohesiveness, and mining the representative cohesive subgraphs is a fundamental problem in graph analysis. The $k$ -truss is one of the most commonly studied cohesive subgraphs,…

Editorial: Digital resource vitalization and urban intelligent computing Open

Hao Sheng, Yang Zhang · 2023

EDITORIAL article Front. Environ. Sci., 15 March 2023Sec. Environmental Informatics and Remote Sensing Volume 11 - 2023 | https://doi.org/10.3389/fenvs.2023.1180305

Fusion and Allocation Network for Light Field Image Super-Resolution Open

Wei Zhang, Wei Ke, Zewei Wu, Zeyu Zhang, Hao Sheng , et al. · 2023

Light field (LF) images taken by plenoptic cameras can record spatial and angular information from real-world scenes, and it is beneficial to fully integrate these two pieces of information to improve image super-resolution (SR). However, …

MPEFT: A novel task scheduling method for workflows Open

Juhua Pu, Qiaolan Meng, Yexuan Chen, Hao Sheng · 2023

Optimizing the scheduling algorithm is a key problem to improving the service efficiency of urban heterogeneous computing platforms. In this paper, we propose a novel list-based scheduling algorithm called Modified Predict Earliest Finish …

Detecting Neighborhood Gentrification at Scale via Street-level Visual Data Open

Tianyuan Huang, Timothy Dai, Zhecheng Wang, Hesu Yoon, Hao Sheng , et al. · 2023

Neighborhood gentrification plays a significant role in shaping the social and economic well-being of both individuals and communities at large. While some efforts have been made to detect gentrification in cities, existing approaches rely…

Learning for Data Synthesis: Joint Local Salient Projection and Adversarial Network Optimization for Vehicle Re-Identification Open

Yanbing Chen, Wei Ke, Wei Zhang, Cui Wang, Hao Sheng , et al. · 2022

The problem of vehicle re-identification in surveillance scenarios has grown in popularity as a research topic. Deep learning has been successfully applied in re-identification tasks in the last few years due to its superior performance. H…

3D zebrafish tracking with topology association Open

Yuan Xu, Yichao Jin, Yang Zhang, Qun‐Xiong Zhu, Yan‐Lin He , et al. · 2022

Recently, zebrafish has received more and more attention due to its wide range of applications such as regeneration promoting therapeutics and drug discovery. Therefore, vision‐based trackers are utilized to record the swimming trajectory …

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