Chandrabose Aravindan

51 papers receiving 444 citations

Peers

Chandrabose Aravindan
Comparison fields: 5 of 88
  • Artificial Intelligence 264
  • Oncology 128
  • Computer Vision and Pattern Recognition 66
  • Information Systems 58
  • Epidemiology 53
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Citations per year

Countries citing papers authored by Chandrabose Aravindan

Since Specialization
Citations

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

Fields of papers citing papers by Chandrabose Aravindan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chandrabose Aravindan

This figure shows the co-authorship network connecting the top 25 collaborators of Chandrabose Aravindan. A scholar is included among the top collaborators of Chandrabose Aravindan 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 Chandrabose Aravindan. Chandrabose Aravindan 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
#WorkIndexed citations
1 84
2
Transformers in Semantic Indexing of Clinical Codes.
3
3 3
4
Early Detection of Anorexia using RNN-LSTM and SVM Classifiers.
4
5
Arabic Author Profiling and Deception Detection using Traditional Learning Methodologies with Word Embedding.
1
6
Extracting Protests from News Using LSTM models with different Attention Mechanisms.
1
7
SSN_NLP@IDAT-FIRE-2019: Irony Detection in Arabic Tweets using Deep Learning and Features-based Approaches.
5
8
Classification of Insincere Questions using SGD Optimization and SVM Classifiers.
1
9
Legal Assistance using Word Embeddings.
6
10
Coral Reef Annotation and Localization using Faster R-CNN
1
11 30
12
Convolutional Long Short-Term Memory Neural Networks for Hierarchical Species Prediction.
2
13
SSN_NLP@IECSIL-FIRE-2018: Deep Learning Approach to Named Entity Recognition and Relation Extraction for Conversational Systems in Indian Languages.
4
14
Deep Learning Approach to English-Tamil and Hindi-Tamil Verb Phrase Translations.
1
15
A Text Similarity Approach for Precedence Retrieval from Legal Documents.
7
16
Decision Tree Approach for Consumer Health Information Search.
0
17 1
18
Artificial Neural Network For The Simultaneous Estimation Of Multicomponent Sample By UV Spectrophotometry
1
19 5
20 18

About Chandrabose Aravindan

Chandrabose Aravindan is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 57 papers that have together received 473 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Logic, Reasoning, and Knowledge (7 papers) and Natural Language Processing Techniques (6 papers). The work is most often cited by research in Artificial Intelligence (264 citations), Oncology (128 citations) and Computer Vision and Pattern Recognition (66 citations). Chandrabose Aravindan has collaborated with scholars based in India, Thailand and United States. Frequent co-authors include S. M. Jaisakthi, P. Mirunalini, R. Rajalakshmi, Rajagopal Appavu, D. Thenmozhi, S. Balakrishnan, K. Kannan, B. Rajesh Kanna, Phan Minh Dũng and Ilkka Niemelä. Their work appears in journals such as Applied Soft Computing, The International Journal of Advanced Manufacturing Technology and Image and Vision Computing.

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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