Jun Sang

1.6k citations
70 papers · 1.2k · 1 hit paper · h-index 17

Impact in

Papers in

Jun Sang

59 papers receiving 1.1k citations

Jun Sang's Hit Papers

Automated Lung Nodule Detection and Classification Using Deep Learning Combined with Multiple Strategies 2019 · 259 citations
2590+2+4Years since publication50100150200250

Peers

Jun Sang
Comparison fields: 5 of 104
  • Computer Vision and Pattern Recognition 438
  • Management Information Systems 128
  • Radiology, Nuclear Medicine and Imaging 256
  • Information Systems 273
  • Health Informatics 12
Replace K. Vijayakumar with:
K. Vijayakumar India
Dheyaa Ahmed Ibrahim Iraq
M. M. A. Hashem Bangladesh
Hani Alshahrani Saudi Arabia
Aaqif Afzaal Abbasi Pakistan
Abul Bashar Saudi Arabia
Salil Bharany India
Haris Pervaiz United Kingdom
Mohammad Alsmirat Jordan
Muhammad Kamran Pakistan
Jun Sang relative to K. Vijayakumar India K. Vijayakumar's profile →
Citations per field
00.5×3.6×
K. Vijayakumar · 1×
Citations per year

Countries citing papers authored by Jun Sang

Since Specialization
Citations

This map shows the geographic impact of Jun Sang'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 Jun Sang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Sang more than expected).

Fields of papers citing papers by Jun Sang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Sang. 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 Jun Sang. The network helps show where Jun Sang may publish in the future.

Co-authors

The 25 scholars most cited alongside Jun Sang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Sang Line = papers co-authored together Jun Sang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Automated Lung Nodule Detection and Classification Using Deep Learning Combined with Multiple Strategies
Hit paper breakdown →
2019259
2 2018168
3 201981
4 202178
5 201762
6 201853
7 202145
8 201942
9 201938
10 201937
11 201828
12 201927
13 201926
14 201824
15 201922
16 201921
17 201717
18 202013
19
Carbon Footprint and Toxicity Indicators of Alternative Chromium Free Tanning in China
20158
20 20227

About Jun Sang

Jun Sang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Information Systems, Radiology, Nuclear Medicine and Imaging and Computer Networks and Communications, having authored 70 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (17 papers), Video Surveillance and Tracking Methods (16 papers), Chaos-based Image/Signal Encryption (15 papers), Anomaly Detection Techniques and Applications (11 papers), Digital Media Forensic Detection (11 papers), Software Engineering Techniques and Practices (7 papers), Software Engineering Research (7 papers) and Retinal Imaging and Analysis (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (438 citations), Management Information Systems (128 citations), Radiology, Nuclear Medicine and Imaging (256 citations), Information Systems (273 citations) and Health Informatics (12 citations). Jun Sang has collaborated with scholars based in China, United States and Saudi Arabia. Frequent co-authors include Haibo Hu, Mohammad S. Alam, Bin Cai, Hong Xiang, Nasrullah Nasrullah, Muhammad Mateen, Muhammad Azeem Akbar, Arif Ali Khan, Zhongyuan Wu and Qian Zhang. Their work appears in journals such as IEEE Access, Sensors, Biomedical Signal Processing and Control, Pattern Recognition Letters and Applied Sciences.

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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