N. V. Subba Reddy

1.5k total citations
76 papers, 993 citations indexed

About

N. V. Subba Reddy is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Organic Chemistry. According to data from OpenAlex, N. V. Subba Reddy has authored 76 papers receiving a total of 993 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 20 papers in Artificial Intelligence and 19 papers in Organic Chemistry. Recurrent topics in N. V. Subba Reddy's work include Handwritten Text Recognition Techniques (14 papers), Vehicle License Plate Recognition (8 papers) and Catalytic C–H Functionalization Methods (7 papers). N. V. Subba Reddy is often cited by papers focused on Handwritten Text Recognition Techniques (14 papers), Vehicle License Plate Recognition (8 papers) and Catalytic C–H Functionalization Methods (7 papers). N. V. Subba Reddy collaborates with scholars based in India, China and United States. N. V. Subba Reddy's co-authors include U. Dinesh Acharya, Ähmed Kamal, Jayant R. Haritsa, Veena Nayak, K. Rajender Reddy, Chandrakant Bagul, G. Sathish Kumar, R. Arun Kumar, Alka Rao and Vunnam Srinivasulu and has published in prestigious journals such as Chemical Communications, The Journal of Urology and BMC Bioinformatics.

In The Last Decade

N. V. Subba Reddy

69 papers receiving 925 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
N. V. Subba Reddy India 18 394 211 188 148 74 76 993
Jiangchao Yao China 19 548 1.4× 201 1.0× 210 1.1× 424 2.9× 18 0.2× 64 1.3k
Bernd Wiswedel Germany 10 62 0.2× 441 2.1× 67 0.4× 203 1.4× 13 0.2× 17 1.1k
Nicolas Cebron Germany 6 49 0.1× 337 1.6× 92 0.5× 196 1.3× 14 0.2× 14 979
Kilian Thiel Germany 7 49 0.1× 338 1.6× 70 0.4× 182 1.2× 12 0.2× 10 942
Thomas R. Gabriel Germany 6 49 0.1× 337 1.6× 57 0.3× 180 1.2× 11 0.1× 9 932
Fabian Dill Germany 3 49 0.1× 337 1.6× 57 0.3× 148 1.0× 11 0.1× 4 895
Zhili Pei China 9 66 0.2× 125 0.6× 70 0.4× 189 1.3× 8 0.1× 30 497
Chunjiang Wu China 9 191 0.5× 148 0.7× 30 0.2× 169 1.1× 6 0.1× 15 514
Shuangjia Zheng China 22 61 0.2× 1.2k 5.5× 137 0.7× 655 4.4× 16 0.2× 46 2.3k

Countries citing papers authored by N. V. Subba Reddy

Since Specialization
Citations

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

Fields of papers citing papers by N. V. Subba Reddy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by N. V. Subba Reddy. 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 N. V. Subba Reddy. The network helps show where N. V. Subba Reddy may publish in the future.

Co-authorship network of co-authors of N. V. Subba Reddy

This figure shows the co-authorship network connecting the top 25 collaborators of N. V. Subba Reddy. A scholar is included among the top collaborators of N. V. Subba Reddy 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 N. V. Subba Reddy. N. V. Subba Reddy 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.
Reddy, N. V. Subba, et al.. (2022). Fake News Detection from Online media using Machine learning Classifiers. Journal of Physics Conference Series. 2161(1). 12027–12027. 20 indexed citations
2.
Reddy, N. V. Subba, et al.. (2022). Comparison of various machine learning approaches uses in heart ailments prediction. Journal of Physics Conference Series. 2161(1). 12010–12010. 8 indexed citations
3.
Jain, Rajat, et al.. (2022). Classification of Cardiac Arrhythmia using improved Feature Selection methods and Ensemble Classifiers. Journal of Physics Conference Series. 2161(1). 12003–12003.
4.
Reddy, N. V. Subba, et al.. (2018). Improving security in Image Steganography using MSB Bit differencing and Cryptographic algorithm. 228–230. 2 indexed citations
5.
Reddy, N. V. Subba, et al.. (2017). Hybrid Architecture for Handwritten Numeral Recognition.
6.
Prema, K. V., et al.. (2017). A novel approach to human gesture recognition. 2017 International Conference On Smart Technologies For Smart Nation (SmartTechCon). 660. 109–115. 1 indexed citations
7.
Kamal, Ähmed, Vijayashree Nayak, Narayana Nagesh, M.V.P.S. Vishnuvardhan, & N. V. Subba Reddy. (2016). Benzo[b]furan derivatives induces apoptosis by targeting the PI3K/Akt/mTOR signaling pathway in human breast cancer cells. Bioorganic Chemistry. 66. 124–131. 31 indexed citations
8.
Kamal, Ähmed, Alka Rao, M.V.P.S. Vishnuvardhan, et al.. (2015). Synthesis of 2-anilinopyridyl–triazole conjugates as antimitotic agents. Organic & Biomolecular Chemistry. 13(17). 4879–4895. 26 indexed citations
9.
Kamal, Ähmed, et al.. (2014). Synthesis and evaluation of N-((1-benzyl-1H-1,2,3-triazol-4-yl)methyl)nicotinamides as potential anticancer agents that inhibit tubulin polymerization. Bioorganic & Medicinal Chemistry. 22(13). 3465–3477. 11 indexed citations
10.
Kamal, Ähmed, Vunnam Srinivasulu, Veena Nayak, et al.. (2014). Design and Synthesis of C3‐Pyrazole/Chalcone‐Linked Beta‐Carboline Hybrids: Antitopoisomerase I, DNA‐Interactive, and Apoptosis‐Inducing Anticancer Agents. ChemMedChem. 9(9). 2084–2098. 81 indexed citations
11.
Kamal, Ähmed, N. V. Subba Reddy, Veena Nayak, et al.. (2013). Synthesis and Biological Evaluation of Benzo[b]furans as Inhibitors of Tubulin Polymerization and Inducers of Apoptosis. ChemMedChem. 9(1). 117–128. 34 indexed citations
12.
Kumar, G. Sathish, R. Arun Kumar, N. V. Subba Reddy, et al.. (2013). Copper catalyzed oxidative coupling of amines with formamides: a new approach for the synthesis of unsymmetrical urea derivatives. Chemical Communications. 49(59). 6686–6686. 44 indexed citations
13.
Reddy, N. V. Subba, et al.. (2012). AmylPepPred: Amyloidogenic Peptide Prediction tool. Bioinformation. 8(20). 994–995. 1 indexed citations
14.
Makkithaya, Krishnamoorthi, N. V. Subba Reddy, & U. Dinesh Acharya. (2008). Improved C-Fuzzy Decision Tree with controllable membership Characteristics for Intrusion Detection. 31(7). 140–145. 1 indexed citations
15.
Urolagin, Siddhaling, K. V. Prema, & N. V. Subba Reddy. (2007). Illumination Invariant Character Recognition Using Binarized Gabor Features. 423–427. 2 indexed citations
16.
Urolagin, Siddhaling, K. V. Prema, & N. V. Subba Reddy. (2007). A Novel Method to Measure the Learning Capability of a Parameter in Artificial Neural Network with Application to Network Freezing. 80. 242–249. 15 indexed citations
17.
Yin, Sheng, Xiaoming Li, Yan Meng, et al.. (2006). Tumor-Suppressive Maspin Regulates Cell Response to Oxidative Stress by Direct Interaction With Glutathione S-Transferase. The Journal of Urology. 175(3). 1172–1172.
18.
Reddy, N. V. Subba & Jayant R. Haritsa. (2005). Analyzing plan diagrams of database query optimizers. Very Large Data Bases. 1228–1239. 56 indexed citations
19.
Reddy, N. V. Subba, et al.. (2002). Neural network based system for script identification in Indian documents. Sadhana. 27(1). 83–97. 64 indexed citations
20.
Reddy, N. V. Subba, et al.. (2002). A neural network based expert system model for conflict resolution. 21. 229–232. 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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