Sumam Mary Idicula
- Human-Computer Interaction top 5%
- Artificial Intelligence top 5%
- Topic Modeling 31
- Natural Language Processing Techniques 31
- Advanced Text Analysis Techniques 15
- Text and Document Classification Technologies 8
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- Handwritten Text Recognition Techniques 9
- Advanced Neural Network Applications 6
- Media Technology top 10%
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- Gene expression and cancer classification 10
- Bioinformatics and Genomic Networks 6
- Journals
- Gene (2 papers)Multimedia Tools and Applications (2 papers)IEEE Geoscience and Remote Sensing Letters (1 paper)
- Partner nations
- IndiaUnited StatesJapan
In The Last Decade
Sumam Mary Idicula
76 papers receiving 561 citations
Peers
Comparison fields: 5 of 84
- Human-Computer Interaction 69
- Artificial Intelligence 279
- Computer Vision and Pattern Recognition 165
- Media Technology 49
- Atmospheric Science 96
Countries citing papers authored by Sumam Mary Idicula
This map shows the geographic impact of Sumam Mary Idicula'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 Sumam Mary Idicula with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumam Mary Idicula more than expected).
Fields of papers citing papers by Sumam Mary Idicula
This network shows the impact of papers produced by Sumam Mary Idicula. 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 Sumam Mary Idicula. The network helps show where Sumam Mary Idicula may publish in the future.
Co-authorship network
The 8 scholars most cited alongside Sumam Mary Idicula, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 0 | |
| 5 | 2021 | 5 | |
| 6 | 2021 | 24 | |
| 7 | 2021 | 2 | |
| 8 | CUSAT NLP@AILA-FIRE2019: Similarity in Legal Texts using Document Level Embeddings. | 2019 | 3 |
| 9 | CUSAT_TEAM@IECSIL-FIRE-2018: A Named Entity Recognition System for Indian Languages. | 2018 | 1 |
| 10 | 2018 | 8 | |
| 11 | 2017 | 1 | |
| 12 | CUSAT_NLP@DPIL-FIRE2016: Malayalam Paraphrase Detection. | 2016 | 2 |
| 13 | CUSAT_TEAM@ DPIL-FIRE2016: Detecting Paraphrase in Indian Languages-Malayalam. | 2016 | 2 |
| 14 | 2015 | 8 | |
| 15 | 2013 | 47 | |
| 16 | 2012 | 13 | |
| 17 | 2012 | 12 | |
| 18 | 2010 | 6 | |
| 19 | A Multilingual Query Processing System using Software Agents | 2007 | 2 |
| 20 | An Empirical Validation of the Cohesion Measure Based on Member Connectivity for Object-Oriented Classes. | 2004 | 1 |
About Sumam Mary Idicula
Sumam Mary Idicula is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Human-Computer Interaction, Signal Processing and Media Technology, having authored 84 papers that have together received 630 indexed citations. Recurring topics across this work include Topic Modeling (31 papers), Natural Language Processing Techniques (31 papers), Advanced Text Analysis Techniques (15 papers), Gene expression and cancer classification (10 papers), Handwritten Text Recognition Techniques (9 papers), Text and Document Classification Technologies (8 papers), Bioinformatics and Genomic Networks (6 papers) and Advanced Neural Network Applications (6 papers). The work is most often cited by research in Human-Computer Interaction (69 citations), Artificial Intelligence (279 citations), Computer Vision and Pattern Recognition (165 citations), Media Technology (49 citations) and Atmospheric Science (96 citations). Sumam Mary Idicula has collaborated with scholars based in India, United States and Japan. Frequent co-authors include U. C. Mohanty, Binu Paul, Someshwar Das, Peter David, U. C. Mohanty, Josette Jones, Enming Zhang and Philip Samuel. Their work appears in journals such as Gene, Multimedia Tools and Applications, IEEE Geoscience and Remote Sensing Letters, Journal of Earth System Science and International Journal of Remote Sensing.
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.