Global Academy of Technology

579 papers receiving 3.9k citations

Peers

Global Academy of Technology
Comparison fields: 5 of 151
  • Health Information Management 300
  • Computer Vision and Pattern Recognition 397
  • Renewable Energy, Sustainability and the Environment 234
  • Artificial Intelligence 478
  • Computer Networks and Communications 287
Replace Dayananda Sagar Academy of Technology and Management with:
Dayananda Sagar Academy of Technology and Management India
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Global Academy of Technology relative to Dayananda Sagar Academy of Technology and Management India Dayananda Sagar Academy of Technology and Management's profile →
Citations per field
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Citations per year

Countries citing scholars working at Global Academy of Technology

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Global Academy of Technology. 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 papers produced at Global Academy of Technology with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Global Academy of Technology more than expected).

Fields of papers published by authors at Global Academy of Technology

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Global Academy of Technology at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Global Academy of Technology at the time of their publication.

About Global Academy of Technology

In recent decades, authors affiliated with Global Academy of Technology have published 729 papers, which have received a total of 3.9k indexed citations . Scholars at this organization have produced 56 papers in Health Information Management, 88 papers in Computer Vision and Pattern Recognition, 68 papers in Computer Networks and Communications, 66 papers in Information Systems and 78 papers in Artificial Intelligence on the topics of Artificial Intelligence in Healthcare (56 papers), Aluminum Alloys Composites Properties (28 papers), AI in cancer detection (22 papers), Advanced Neural Network Applications (21 papers), Energy Efficient Wireless Sensor Networks (20 papers), Cloud Computing and Resource Management (17 papers), Smart Agriculture and AI (16 papers) and Natural Fiber Reinforced Composites (16 papers). Their work is cited by papers focused on Health Information Management (300 citations), Computer Vision and Pattern Recognition (397 citations), Renewable Energy, Sustainability and the Environment (234 citations), Artificial Intelligence (478 citations) and Computer Networks and Communications (287 citations). Authors at Global Academy of Technology collaborate with scholars in India, United States and Saudi Arabia and have published in prestigious journals including Journal of Coastal Research, Scientific Reports, Journal of Thermal Analysis and Calorimetry, Wireless Personal Communications and Journal of Materials Science Materials in Electronics. Some of Global Academy of Technology's most productive authors include Ashwini Kodipalli, Thammadihalli Nanjundaiah Ravishankar, Santosh K. Dasar, Trupthi Rao, Roshan Joy Martis, Thippeswamy Ramakrishnappa, Sérgio R. Teixeira, Pavan Chakraborty, Jobish Johns and Steven Lawrence Fernandes.

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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