S. M. Anzar

449 total citations
42 papers, 219 citations indexed

About

S. M. Anzar is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, S. M. Anzar has authored 42 papers receiving a total of 219 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 13 papers in Signal Processing and 12 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in S. M. Anzar's work include Biometric Identification and Security (11 papers), Digital Imaging for Blood Diseases (6 papers) and Retinal Imaging and Analysis (6 papers). S. M. Anzar is often cited by papers focused on Biometric Identification and Security (11 papers), Digital Imaging for Blood Diseases (6 papers) and Retinal Imaging and Analysis (6 papers). S. M. Anzar collaborates with scholars based in India, United Arab Emirates and Russia. S. M. Anzar's co-authors include Alavikunhu Panthakkan, Wathiq Mansoor, Hussain Al-Ahmad, Saeed Al Mansoori, P. S. Sathidevi, Ashwin Mohan, H.C. Reddy and Fatma Taher and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Computers in Biology and Medicine.

In The Last Decade

S. M. Anzar

28 papers receiving 191 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
S. M. Anzar India	9	77	67	53	51	44	42	219
Min Beom Lee South Korea	8	175 2.3×	146 2.2×	153 2.9×	85 1.7×	30 0.7×	11	376
Meilu Zhu Hong Kong	8	143 1.9×	119 1.8×	68 1.3×	47 0.9×	24 0.5×	27	305
S. Saraswathi India	9	58 0.8×	108 1.6×	9 0.2×	34 0.7×	44 1.0×	33	228
Masum Shah Junayed Türkiye	10	121 1.6×	66 1.0×	108 2.0×	7 0.1×	57 1.3×	26	340
Anurag Gupta India	9	19 0.2×	97 1.4×	33 0.6×	83 1.6×	13 0.3×	31	276
Saif Ur Rehman Khan China	13	106 1.4×	136 2.0×	112 2.1×	16 0.3×	18 0.4×	31	363
José Marquês Soares Brazil	9	90 1.2×	71 1.1×	155 2.9×	26 0.5×	32 0.7×	30	427
Paolo Andreini Italy	10	116 1.5×	76 1.1×	43 0.8×	7 0.1×	13 0.3×	22	246
Klaus Schöffmann Austria	9	276 3.6×	81 1.2×	27 0.5×	25 0.5×	25 0.6×	13	352
Thang Doan Canada	5	45 0.6×	120 1.8×	43 0.8×	6 0.1×	65 1.5×	6	202

Countries citing papers authored by S. M. Anzar

Since Specialization

Citations

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

Fields of papers citing papers by S. M. Anzar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. M. Anzar. 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 S. M. Anzar. The network helps show where S. M. Anzar may publish in the future.

Co-authorship network of co-authors of S. M. Anzar

This figure shows the co-authorship network connecting the top 25 collaborators of S. M. Anzar. A scholar is included among the top collaborators of S. M. Anzar 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 S. M. Anzar. S. M. Anzar 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

Anzar, S. M., et al.. (2025). Deep Learning Transformers for Sentiment Classification: A Performance Evaluation. 1–6.

Anzar, S. M., et al.. (2025). Evaluation of UAV-Based RGB and Multispectral Vegetation Indices for Precision Agriculture in Palm Tree Cultivation. The international archives of the photogrammetry, remote sensing and spatial information sciences. XLVIII-G-2025. 163–170. 1 indexed citations

Panthakkan, Alavikunhu, S. M. Anzar, Wathiq Mansoor, & Hussain Al-Ahmad. (2024). A new frontier in hematology: Robust deep learning ensembles for white blood cell classification. Biomedical Signal Processing and Control. 100. 106995–106995. 5 indexed citations

Anzar, S. M., et al.. (2024). Touchless fingerprint recognition: A survey of recent developments and challenges. Computers & Electrical Engineering. 122. 109894–109894.

Anzar, S. M., et al.. (2024). The robust SmartEnsembleNet: A game changer in finger knuckle biometrics. Expert Systems with Applications. 255. 124810–124810. 5 indexed citations

Panthakkan, Alavikunhu, et al.. (2024). AI-Driven Solutions for Falcon Disease Classification: Concatenated ConvNeXt cum EfficientNet AI Model Approach. ArXiv.org. 1–5. 1 indexed citations

Anzar, S. M., et al.. (2024). Fine-Tuning Large Language Models for Task Specific Data. 1–6.

Panthakkan, Alavikunhu, S. M. Anzar, Saeed Al Mansoori, & Hussain Al-Ahmad. (2023). Preserving the Integrity of Hyperspectral Satellite Imagery Using a Secure and Efficient Reversible Watermarking Technique for Ownership Protection. 1–5.

Anzar, S. M., et al.. (2022). Machine learning based system identification of a realistic heat integrated distillation column using particle swarm optimization. Chemical Engineering Communications. 210(10). 1694–1714. 2 indexed citations

10.

Anzar, S. M., et al.. (2022). Mask R-CNN with Multi-Backbones - A Comparative Analysis. 55–60. 5 indexed citations

11.

Panthakkan, Alavikunhu, et al.. (2022). Concatenated Xception-ResNet50 — A novel hybrid approach for accurate skin cancer prediction. Computers in Biology and Medicine. 150. 106170–106170. 47 indexed citations

12.

Panthakkan, Alavikunhu, S. M. Anzar, Saeed Al Mansoori, Wathiq Mansoor, & Hussain Al-Ahmad. (2022). A systematic comparison of transfer learning models for COVID-19 prediction. Intelligent Decision Technologies. 16(3). 557–574. 1 indexed citations

13.

Anzar, S. M., et al.. (2021). A comprehensive review on automated systems for severity grading of diabetic retinopathy and macular edema. International Journal of Imaging Systems and Technology. 31(4). 2093–2122. 10 indexed citations

14.

Anzar, S. M., et al.. (2021). Random Interval Attendance Management System (RIAMS): A Novel Multimodal Approach for Post-COVID Virtual Learning. IEEE Access. 9. 91001–91016. 8 indexed citations

15.

Panthakkan, Alavikunhu, S. M. Anzar, Saeed Al Mansoori, & Hussain Al-Ahmad. (2021). A novel DeepNet model for the efficient detection of COVID-19 for symptomatic patients. Biomedical Signal Processing and Control. 68. 102812–102812. 13 indexed citations

16.

Panthakkan, Alavikunhu, S. M. Anzar, Saeed Al Mansoori, & Hussain Al-Ahmad. (2020). Accurate Prediction of COVID-19 (+) Using AI Deep VGG16 Model. 1–4. 12 indexed citations

17.

Anzar, S. M., et al.. (2020). Efficient wavelet based scale invariant feature transform for partial face recognition. AIP conference proceedings. 2222. 30017–30017. 4 indexed citations

18.

Anzar, S. M., et al.. (2017). Robust partial fingerprint recognition using wavelet SIFT descriptors. Pattern Analysis and Applications. 20(4). 963–979. 17 indexed citations

19.

Anzar, S. M. & P. S. Sathidevi. (2014). On combining multi-normalization and ancillary measures for the optimal score level fusion of fingerprint and voice biometrics. EURASIP Journal on Advances in Signal Processing. 2014(1). 4 indexed citations

20.

Anzar, S. M. & P. S. Sathidevi. (2014). Optimal score level fusion combining multi-normalisation and separability measures. 1(2). 127–127.

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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