Anand Paul

2.1k total citations · 1 hit paper
73 papers, 1.2k citations indexed

About

Anand Paul is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Anand Paul has authored 73 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 18 papers in Artificial Intelligence and 15 papers in Computer Networks and Communications. Recurrent topics in Anand Paul's work include IoT and Edge/Fog Computing (12 papers), Advanced Neural Network Applications (9 papers) and Video Surveillance and Tracking Methods (7 papers). Anand Paul is often cited by papers focused on IoT and Edge/Fog Computing (12 papers), Advanced Neural Network Applications (9 papers) and Video Surveillance and Tracking Methods (7 papers). Anand Paul collaborates with scholars based in South Korea, India and United States. Anand Paul's co-authors include Rathinaraja Jeyaraj, Jeonghong Kim, Jun‐Hyun Park, Jae‐Mo Kang, Sangseok Yun, Hasnain Ali Shah, Bekhzod Olimov, Seungmin Rho, Anand Nayyar and Arun Solanki and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Nano Energy.

In The Last Decade

Anand Paul

65 papers receiving 1.2k citations

Hit Papers

A Robust Approach for Bra... 2022 2026 2023 2024 2022 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anand Paul South Korea 19 310 279 240 226 220 73 1.2k
S. Baskar India 22 384 1.2× 320 1.1× 287 1.2× 440 1.9× 316 1.4× 72 1.6k
Sandeep Kumar India 23 341 1.1× 444 1.6× 124 0.5× 224 1.0× 210 1.0× 118 1.5k
Fahd N. Al‐Wesabi Saudi Arabia 20 537 1.7× 392 1.4× 251 1.0× 426 1.9× 239 1.1× 167 1.7k
Anwer Mustafa Hilal Saudi Arabia 19 451 1.5× 298 1.1× 119 0.5× 332 1.5× 164 0.7× 150 1.3k
Wathiq Mansoor United Arab Emirates 22 441 1.4× 266 1.0× 262 1.1× 296 1.3× 251 1.1× 177 1.6k
Arpit Jain India 22 263 0.8× 315 1.1× 174 0.7× 341 1.5× 247 1.1× 100 1.4k
Anandakumar Haldorai India 15 224 0.7× 254 0.9× 129 0.5× 321 1.4× 217 1.0× 76 1.0k
Abdulmajeed Alsufyani Saudi Arabia 19 289 0.9× 290 1.0× 110 0.5× 211 0.9× 150 0.7× 50 1.1k
Ankit Kumar India 20 254 0.8× 250 0.9× 308 1.3× 280 1.2× 137 0.6× 184 1.3k
G. Ramkumar India 29 407 1.3× 343 1.2× 535 2.2× 409 1.8× 267 1.2× 200 2.4k

Countries citing papers authored by Anand Paul

Since Specialization
Citations

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

Fields of papers citing papers by Anand Paul

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anand Paul

This figure shows the co-authorship network connecting the top 25 collaborators of Anand Paul. A scholar is included among the top collaborators of Anand Paul 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 Anand Paul. Anand Paul 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.
Albelwi, Saleh, et al.. (2025). A Deep Sparse Capsule Network for Non-Invasive Blood Glucose Level Estimation Using a PPG Sensor. Sensors. 25(6). 1868–1868. 1 indexed citations
2.
Ali, Wajid, Awais Ahmad, Muhammad Shahid Iqbal, et al.. (2024). Enhancing COVID‐19 misinformation detection through novel attention mechanisms in NLP. Expert Systems. 42(1).
3.
Kuriachen, Basil, et al.. (2024). Defect detection in fused deposition modelling using lightweight convolutional neural networks. Engineering Applications of Artificial Intelligence. 141. 109802–109802. 2 indexed citations
4.
Rehman, Abdul, Faisal Saeed, M. Mazhar Rathore, Anand Paul, & Jae‐Mo Kang. (2024). Smart city fire surveillance: A deep state‐space model with intelligent agents. SHILAP Revista de lepidopterología. 6(3). 199–210. 2 indexed citations
5.
Rehman, Abdul, Dongsun Kim, & Anand Paul. (2023). Convolutional Neural Network Model for Fire Detection in Real-Time Environment. Computers, materials & continua/Computers, materials & continua (Print). 77(2). 2289–2307. 7 indexed citations
6.
Natarajan, Yuvaraj, Girish Wadhwa, K. R. Sri Preethaa, & Anand Paul. (2023). Forecasting Carbon Dioxide Emissions of Light-Duty Vehicles with Different Machine Learning Algorithms. Electronics. 12(10). 2288–2288. 25 indexed citations
7.
Jeyaraj, Rathinaraja, et al.. (2023). DeepWalk with Reinforcement Learning (DWRL) for node embedding. Expert Systems with Applications. 243. 122819–122819. 5 indexed citations
8.
Jeyaraj, Rathinaraja & Anand Paul. (2022). Optimizing MapReduce Task Scheduling on Virtualized Heterogeneous Environments Using Ant Colony Optimization. IEEE Access. 10. 55842–55855. 17 indexed citations
9.
Jeyaraj, Rathinaraja, et al.. (2022). Resource Management in Cloud and Cloud-influenced Technologies for Internet of Things Applications. ACM Computing Surveys. 55(12). 1–37. 38 indexed citations
10.
Riaz, Rabia, et al.. (2022). Secure Healthcare Record Sharing Mechanism with Blockchain. Applied Sciences. 12(5). 2307–2307. 34 indexed citations
11.
Daniel, Alfred, et al.. (2022). Blockchain Technologies: Smart Contracts for Consumer Electronics Data Sharing and Secure Payment. Electronics. 12(1). 208–208. 16 indexed citations
12.
Jeyaraj, Rathinaraja, et al.. (2021). Handling Non-Local Executions to Improve MapReduce Performance Using Ant Colony Optimization. IEEE Access. 9. 96176–96188. 6 indexed citations
13.
Karthigaikumar, P., et al.. (2021). Efficient Morphological Segmentation of Brain Hemorrhage Stroke Lesion Through MultiResUNet. Computers, materials & continua/Computers, materials & continua (Print). 70(3). 5233–5249. 1 indexed citations
14.
Olimov, Bekhzod, et al.. (2021). FU-Net: fast biomedical image segmentation model based on bottleneck convolution layers. Multimedia Systems. 27(4). 637–650. 31 indexed citations
15.
Saeed, Faisal, et al.. (2021). A robust approach for industrial small-object detection using an improved faster regional convolutional neural network. Scientific Reports. 11(1). 23390–23390. 26 indexed citations
16.
Rizvi, Sanam Shahla, et al.. (2020). A Cloud-Based Enterprise Resource Planning Architecture for Women’s Education in Remote Areas. Electronics. 9(11). 1758–1758. 4 indexed citations
17.
Jeyaraj, Rathinaraja, V. S. Ananthanarayana, & Anand Paul. (2020). Improving MapReduce scheduler for heterogeneous workloads in a heterogeneous environment. Concurrency and Computation Practice and Experience. 32(17). 2 indexed citations
18.
Li, Xingwang, Mengyan Huang, Yuanwei Liu, et al.. (2020). I/Q Imbalance Aware Nonlinear Wireless-Powered Relaying of B5G Networks: Security and Reliability Analysis. IEEE Transactions on Network Science and Engineering. 8(4). 2995–3008. 68 indexed citations
20.
Paul, Anand, Gary Levy, & Paul D. Greig. (1993). Balancing cyclosporine A nephrotoxicity and rejection late after adult liver transplantation.. PubMed. 25(4). 2664–5. 2 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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