Anup Majumder

701 total citations
24 papers, 369 citations indexed

About

Anup Majumder is a scholar working on Oncology, Plant Science and Molecular Biology. According to data from OpenAlex, Anup Majumder has authored 24 papers receiving a total of 369 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Oncology, 4 papers in Plant Science and 3 papers in Molecular Biology. Recurrent topics in Anup Majumder's work include Smart Agriculture and AI (4 papers), Identification and Quantification in Food (3 papers) and Cutaneous Melanoma Detection and Management (3 papers). Anup Majumder is often cited by papers focused on Smart Agriculture and AI (4 papers), Identification and Quantification in Food (3 papers) and Cutaneous Melanoma Detection and Management (3 papers). Anup Majumder collaborates with scholars based in Bangladesh, India and Japan. Anup Majumder's co-authors include Md. Tarek Habib, Al Amin Biswas, Morium Akter, Farruk Ahmed, Mohammad Shorif Uddin, Aditya Rajbongshi, Md. Jueal Mia, Md. Mahfujur Rahman, Md. Mahbubur Rahman and F. M. Javed Mehedi Shamrat and has published in prestigious journals such as SHILAP Revista de lepidopterología, Astronomy and Astrophysics and Journal of King Saud University - Computer and Information Sciences.

In The Last Decade

Anup Majumder

24 papers receiving 346 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anup Majumder Bangladesh 11 150 70 65 58 54 24 369
Aboul Ella Hassenian Egypt 6 118 0.8× 67 1.0× 109 1.7× 76 1.3× 19 0.4× 7 315
Rabbia Mahum Pakistan 12 147 1.0× 67 1.0× 140 2.2× 235 4.1× 31 0.6× 35 683
Emine Uçar Türkiye 7 482 3.2× 187 2.7× 95 1.5× 59 1.0× 8 0.1× 16 761
Zaidah Ibrahim Malaysia 14 180 1.2× 78 1.1× 96 1.5× 176 3.0× 13 0.2× 65 596
Mohib Ullah Pakistan 11 52 0.3× 9 0.1× 175 2.7× 107 1.8× 37 0.7× 47 374
Janmejay Pant India 7 82 0.5× 19 0.3× 50 0.8× 18 0.3× 8 0.1× 50 261
D.C. Joy Winnie Wise India 6 61 0.4× 30 0.4× 46 0.7× 34 0.6× 16 0.3× 19 220
Emine Cengil Türkiye 14 43 0.3× 17 0.2× 98 1.5× 103 1.8× 19 0.4× 29 329
K. Ashokkumar India 8 140 0.9× 48 0.7× 42 0.6× 27 0.5× 5 0.1× 23 292

Countries citing papers authored by Anup Majumder

Since Specialization
Citations

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

Fields of papers citing papers by Anup Majumder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anup Majumder

This figure shows the co-authorship network connecting the top 25 collaborators of Anup Majumder. A scholar is included among the top collaborators of Anup Majumder 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 Anup Majumder. Anup Majumder 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.
Brienza, M., K. Rajpurohit, E. Churazov, et al.. (2025). Non-thermal filaments and AGN recurrent activity in the galaxy group Nest200047: A LOFAR, uGMRT, MeerKAT, and VLA radio spectral analysis. Astronomy and Astrophysics. 696. A239–A239. 4 indexed citations
2.
Majumder, Anup, et al.. (2023). An in-depth analysis of Convolutional Neural Network architectures with transfer learning for skin disease diagnosis. SHILAP Revista de lepidopterología. 3. 100143–100143. 42 indexed citations
3.
Rajbongshi, Aditya, et al.. (2022). A Comprehensive Investigation to Cauliflower Diseases Recognition: An Automated Machine Learning Approach. International Journal on Advanced Science Engineering and Information Technology. 12(1). 32–41. 19 indexed citations
4.
Azad, Md. Abul Kalam, et al.. (2021). Improving signal detection accuracy at FC of a CRN using machine learning and fuzzy rules. Indonesian Journal of Electrical Engineering and Computer Science. 21(2). 1140–1140. 6 indexed citations
5.
Biswas, Al Amin, et al.. (2021). Recognition of Local Birds using Different CNN Architectures with Transfer Learning. 1–6. 14 indexed citations
6.
Rabbani, Masud, et al.. (2021). Skin Disease Recognition: A Machine Vision Based Approach. 1029–1034. 11 indexed citations
7.
Shamrat, F. M. Javed Mehedi, et al.. (2020). A Smart Automated System Model For Vehicles Detection To Maintain Traffic By Image Processing. International journal of scientific and technology research. 9(2). 2921–2928. 13 indexed citations
8.
Rajbongshi, Aditya, et al.. (2020). Bangla Optical Character Recognition and Text-to-Speech Conversion using Raspberry Pi. International Journal of Advanced Computer Science and Applications. 11(6). 10 indexed citations
9.
Shamrat, F. M. Javed Mehedi, Zarrin Tasnim, Pronab Ghosh, Anup Majumder, & Md. Zahid Hasan. (2020). Personalization of Job Circular Announcement to Applicants Using Decision Tree Classification Algorithm. 2020 IEEE International Conference for Innovation in Technology (INOCON). 1–5. 21 indexed citations
10.
Biswas, Al Amin, Md. Jueal Mia, & Anup Majumder. (2019). Forecasting the Number of Road Accidents and Casualties using Random Forest Regression in the Context of Bangladesh. 1–5. 10 indexed citations
11.
Alam, Md. Mahbub, et al.. (2019). Predicting and Staging Chronic Kidney Disease of Diabetes (Type-2) Patient using Machine Learning Algorithms. International Journal of Innovative Technology and Exploring Engineering. 8(12). 260–209. 2 indexed citations
12.
Biswas, Al Amin, et al.. (2019). Predicting the Enrollment and Dropout of Students in the Post-Graduation Degree using Machine Learning Classifier. International Journal of Innovative Technology and Exploring Engineering. 8(11). 3083–3088. 9 indexed citations
13.
Mia, Md. Jueal, et al.. (2019). Computer Vision Based Local Fruit Recognition. International Journal of Engineering and Advanced Technology. 9(1). 2810–2820. 24 indexed citations
14.
Majumder, Anup, et al.. (2019). Complexity Analysis and Accuracy of Image Recovery Based on Signal Transformation Algorithms. International Journal of Innovative Technology and Exploring Engineering. 9(1). 1607–1612. 2 indexed citations
15.
16.
Habib, Md. Tarek, et al.. (2018). Machine vision based papaya disease recognition. Journal of King Saud University - Computer and Information Sciences. 32(3). 300–309. 118 indexed citations
17.
Majumder, Anup, et al.. (2013). Radical treatment of locally advanced head and neck cancer with concurrent chemo radiation-cisplatin versus carboplatin: A randomized comparative phase III trial. Clinical Cancer Investigation Journal. 2(2). 122–122. 1 indexed citations
18.
Sarkar, Supriya, et al.. (2010). Unilateral Massive Pleural Effusion: A Presentation of Unsuspected Multiple Myeloma. Indian Journal of Hematology and Blood Transfusion. 26(2). 62–64. 7 indexed citations
19.
Basu, Siddhartha, et al.. (2008). Papillary carcinoma of thyroid in a 11 months old child. Indian Journal of Medical and Paediatric Oncology. 29(2). 33–35. 3 indexed citations
20.
Majumder, Anup. (1980). Computer Analysis of Frequency Spectrum of the Phonopulmogram. PubMed Central. 1. 266–271. 1 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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