Ashok Samal

6.1k total citations · 1 hit paper
162 papers, 4.3k citations indexed

About

Ashok Samal is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Ashok Samal has authored 162 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 41 papers in Computer Vision and Pattern Recognition and 35 papers in Signal Processing. Recurrent topics in Ashok Samal's work include Data Management and Algorithms (20 papers), Smart Agriculture and AI (15 papers) and Image Retrieval and Classification Techniques (14 papers). Ashok Samal is often cited by papers focused on Data Management and Algorithms (20 papers), Smart Agriculture and AI (15 papers) and Image Retrieval and Classification Techniques (14 papers). Ashok Samal collaborates with scholars based in United States, India and China. Ashok Samal's co-authors include D. Chaudhuri, Leen‐Kiat Soh, David B. Marx, George E. Meyer, Sharad Seth, Sruti Das Choudhury, Jordan R. Green, Tala Awada, David D. Jones and Govindarajan Konda Naganathan and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Ashok Samal

156 papers receiving 4.0k citations

Hit Papers

Automatic recognition and analysis of human faces and fac... 1992 2026 2003 2014 1992 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ashok Samal United States 32 1.3k 678 617 539 493 162 4.3k
Graham W. Taylor Canada 26 2.3k 1.7× 1.6k 2.4× 292 0.5× 364 0.7× 80 0.2× 101 5.5k
Xiaohui Yuan United States 36 1.9k 1.4× 949 1.4× 323 0.5× 146 0.3× 99 0.2× 225 5.5k
Bing Shuai Singapore 17 2.4k 1.8× 1.6k 2.3× 257 0.4× 317 0.6× 191 0.4× 31 5.8k
Jiuxiang Gu United States 16 2.0k 1.5× 1.6k 2.4× 242 0.4× 301 0.6× 178 0.4× 42 5.3k
Lianyang Ma China 5 1.5k 1.1× 1.2k 1.8× 240 0.4× 279 0.5× 177 0.4× 11 4.6k
Jason Kuen United States 14 2.0k 1.5× 1.4k 2.0× 246 0.4× 284 0.5× 179 0.4× 24 5.3k
Zhenhua Wang China 15 2.6k 2.0× 1.4k 2.0× 252 0.4× 283 0.5× 179 0.4× 50 6.0k
Jing‐Hao Xue United Kingdom 36 2.8k 2.1× 1.0k 1.5× 268 0.4× 294 0.5× 107 0.2× 185 4.7k
Chuan‐Yu Chang Taiwan 31 984 0.7× 834 1.2× 358 0.6× 266 0.5× 125 0.3× 228 3.6k
Abdelhameed Ibrahim‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬ Egypt 42 699 0.5× 1.6k 2.4× 171 0.3× 269 0.5× 183 0.4× 160 4.9k

Countries citing papers authored by Ashok Samal

Since Specialization
Citations

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

Fields of papers citing papers by Ashok Samal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashok Samal

This figure shows the co-authorship network connecting the top 25 collaborators of Ashok Samal. A scholar is included among the top collaborators of Ashok Samal 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 Ashok Samal. Ashok Samal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bhagat, Kaushal Kumar, et al.. (2025). Analyzing the discourse on open educational resources on Twitter: a sentiment analysis approach. Educational Technology Research and Development. 73(3). 1297–1320. 1 indexed citations
2.
Choudhury, Sruti Das, et al.. (2024). Stress phenotyping analysis leveraging autofluorescence image sequences with machine learning. Frontiers in Plant Science. 15. 2 indexed citations
3.
Choudhury, Sruti Das, et al.. (2023). EmergeNet: A novel deep-learning based ensemble segmentation model for emergence timing detection of coleoptile. Frontiers in Plant Science. 14. 1084778–1084778. 3 indexed citations
4.
Muñoz‐Arriola, Francisco, et al.. (2021). Multi-feature data repository development and analytics for image cosegmentation in high-throughput plant phenotyping. PLoS ONE. 16(9). e0257001–e0257001. 8 indexed citations
5.
Lim, Phui Cheng, et al.. (2021). Deep-Learning-Based Multivariate Pattern Analysis (dMVPA): A Tutorial and a Toolbox. Frontiers in Human Neuroscience. 15. 638052–638052. 5 indexed citations
6.
Choudhury, Sruti Das, et al.. (2020). Leveraging Image Analysis to Compute 3D Plant Phenotypes Based on Voxel-Grid Plant Reconstruction. Frontiers in Plant Science. 11. 521431–521431. 43 indexed citations
7.
Samal, Ashok, et al.. (2020). Paired Trial Classification: A Novel Deep Learning Technique for MVPA. Frontiers in Neuroscience. 14. 417–417. 5 indexed citations
8.
Choudhury, Sruti Das, Ashok Samal, & Tala Awada. (2019). Leveraging Image Analysis for High-Throughput Plant Phenotyping. Frontiers in Plant Science. 10. 508–508. 124 indexed citations
9.
Choudhury, Sruti Das, et al.. (2018). Holistic and component plant phenotyping using temporal image sequence. Plant Methods. 14(1). 35–35. 54 indexed citations
10.
Yu, Jin-Gang, Gui-Song Xia, Changxin Gao, & Ashok Samal. (2015). A Computational Model for Object-Based Visual Saliency: Spreading Attention Along Gestalt Cues. IEEE Transactions on Multimedia. 18(2). 273–286. 23 indexed citations
11.
Wang, Jun, Ashok Samal, & Jordan R. Green. (2014). Preliminary Test of a Real-Time, Interactive Silent Speech Interface Based on Electromagnetic Articulograph. 38–45. 24 indexed citations
12.
Cluff, Kim, Govindarajan Konda Naganathan, Jeyamkondan Subbiah, Ashok Samal, & Chris R. Calkins. (2013). Optical scattering with hyperspectral imaging to classify longissimus dorsi muscle based on beef tenderness using multivariate modeling. Meat Science. 95(1). 42–50. 27 indexed citations
13.
Nugent, Gwen, et al.. (2011). A Learning Analytic Approach to Identify Attributes of Learners and Multimedia Instruction that Influence Learning. EdMedia: World Conference on Educational Media and Technology. 2011(1). 2021–2028. 2 indexed citations
14.
Bhatia, Sanjiv, et al.. (2011). Effect of font size, italics, and colour count on web usability. International Journal of Computational Vision and Robotics. 2(2). 156–156. 18 indexed citations
15.
Wang, Jun, et al.. (2010). Vowel Recognition from Continuous Articulatory\nMovements for Speaker-Dependent Applications. Insecta mundi. 7 indexed citations
16.
Marx, David B., et al.. (2007). Spatial Clustering Using the Likelihood Function. 637–642. 3 indexed citations
17.
Shi, Jun, Ashok Samal, & David B. Marx. (2006). How effective are landmarks and their geometry for face recognition?. Computer Vision and Image Understanding. 102(2). 117–133. 98 indexed citations
18.
Nugent, Gwen, Leen‐Kiat Soh, & Ashok Samal. (2006). Design, Development, and Validation of Learning Objects. Journal of Educational Technology Systems. 34(3). 271–281. 20 indexed citations
19.
Soh, Leen‐Kiat, et al.. (2005). Analyzing relationships between closed labs and course activities in CS1. 183–187. 6 indexed citations
20.
Henderson, Thomas C. & Ashok Samal. (1986). Shape grammar compilers. Pattern Recognition. 19(4). 279–288. 5 indexed citations

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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