Shifeng Wang

516 total citations
64 papers, 346 citations indexed

About

Shifeng Wang is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Environmental Engineering. According to data from OpenAlex, Shifeng Wang has authored 64 papers receiving a total of 346 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computer Vision and Pattern Recognition, 23 papers in Aerospace Engineering and 16 papers in Environmental Engineering. Recurrent topics in Shifeng Wang's work include Robotics and Sensor-Based Localization (18 papers), Remote Sensing and LiDAR Applications (14 papers) and Advanced Neural Network Applications (12 papers). Shifeng Wang is often cited by papers focused on Robotics and Sensor-Based Localization (18 papers), Remote Sensing and LiDAR Applications (14 papers) and Advanced Neural Network Applications (12 papers). Shifeng Wang collaborates with scholars based in China, Australia and Saudi Arabia. Shifeng Wang's co-authors include Yixiang Yue, Lu Tong, Leishan Zhou, M. Rapik Saat, Sarath Kodagoda, Lei Shi, Hualin Wang, Jin Meng, Xiang Dai and Hazrat Bilal and has published in prestigious journals such as PLoS ONE, Chemical Engineering Journal and IEEE Access.

In The Last Decade

Shifeng Wang

52 papers receiving 334 citations

Peers

Countries citing papers authored by Shifeng Wang

Since Specialization

Citations

This map shows the geographic impact of Shifeng Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shifeng Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shifeng Wang more than expected).

Fields of papers citing papers by Shifeng Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shifeng Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shifeng Wang. The network helps show where Shifeng Wang may publish in the future.

Co-authorship network of co-authors of Shifeng Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Shifeng Wang. A scholar is included among the top collaborators of Shifeng Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shifeng Wang. Shifeng Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Title	Journal	Authors	Indexed citations
1	DSQN: Robust path planning of mobile robot based on deep spiking Q-network	Neurocomputing	Aakash Kumar, Lei Zhang et al.	4
2	Deep reinforcement learning for robust robot navigation in complex and crowded environments	Journal of King Saud University - Computer and Information Sciences	Shifeng Wang, Aakash Kumar et al.	0
3	Bone marrow mesenchymal stem cells alleviate neurological dysfunction by reducing autophagy damage via downregulation of SYNPO2 in neonatal hypoxic–ischemic encephalopathy rats	Cell Death and Disease	Jie Cheng, Ruo‐Lan Du et al.	5
4	NDF-SLAM: LiDAR SLAM based on neural distance field for registration and loop closure detection	Measurement	Hang Yang, Aakash Kumar et al.	0
5	Three-Dimensional Environment Mapping with a Rotary-Driven Lidar in Real Time	Sensors	Bo Lü, Yan Li et al.	0
6	TS-LCD: Two-Stage Loop-Closure Detection Based on Heterogeneous Data Fusion	Sensors	Xin Meng, Jonghyuk Kim et al.	2
7	Comprehensive Improvement of Binocular Structured Light Calibration Method Based on Radical-Conservative Cooperative Particle Swarm	Sensors	Jun Ma, Shifeng Wang et al.	0
8	Research on Robot Path Planning Technology by Integrating Particle Swarm Optimization Algorithm and DWA Algorithm		Shifeng Wang et al.	1
9	Building on prior lightweight CNN model combined with LSTM-AM framework to guide fault detection in fixed-wing UAVs	International Journal of Machine Learning and Cybernetics	Aakash Kumar, Shifeng Wang et al.	20
10	Accurate localization of indoor high similarity scenes using visual slam combined with loop closure detection algorithm	PLoS ONE	Jin Meng, Yan Li et al.	1
11	STFNET: Sparse Temporal Fusion for 3D Object Detection in LiDAR Point Cloud	IEEE Sensors Journal	Xin Meng, Jun Ma et al.	2
12	A phase error compensation method for three-dimensional shape measurement using improved iteration algorithm	Journal of Modern Optics	Xin Meng, Shifeng Wang et al.	0
13	Path Planning Algorithm of Mobile Robot Based on Improved Q-learning Algorithm		Feng Qian, Tiankai Chen et al.	1
14	A Model for Urban Environment Instance Segmentation with Data Fusion	Sensors	Jin Meng, Shifeng Wang et al.	2
15	An Integrated Multi-Channel Deep Neural Network for Mesial Temporal Lobe Epilepsy Identification Using Multi-Modal Medical Data	Bioengineering	Xuan Ji, Shifeng Wang et al.	2
16	PVONet: point-voxel-based semi-supervision monocular three-dimensional object detection using LiDAR camera systems	Journal of Electronic Imaging	Shifeng Wang et al.	2
17	Lidar Point Semantic Segmentation Using Dual Attention Mechanism	Journal of Russian Laser Research	Tiankai Chen, Feng Qian et al.	1
18	Three-Dimensional Reconstruction Algorithm for Facial Plastic Surgery using High-Precision Monocular Structured Light		Peng Zhang, Shifeng Wang et al.	1
19	Semantic Segmentation Algorithms for Ground AGV and UAV Medical Transport Scenes		Tiankai Chen, Shifeng Wang et al.	1
20	Design and Implementation of PDA-based Public Transportation System	Jisuanji yingyong yanjiu	Shifeng Wang	1

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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