Zobrazeno 1 - 10
of 2 649
pro vyhledávání: '"Koundinya"'
Autor:
Shiva Shankar, Devadoss Kumar, Jaiswal Deepa, Karuthapandi Madasamy, Shrikant Jadhav, Kalyani B. Kunte
Publikováno v:
Journal of Insect Biodiversity and Systematics, Vol 9, Iss 3, Pp 449-467 (2023)
The present investigation was carried out to study the fauna of aquatic beetles of Koundinya wildlife sanctuary (India). A total of forty two species belonging to four families was recorded. The highest number of species was found in the family Dytis
Externí odkaz:
https://doaj.org/article/eb10d6298a104428bfe2ab69b542d13e
Autor:
Shankar, Shiva1 cshivashankarchinna@gmail.com, Kumar, Devadoss1 kumar@vhnsnc.edu.in, Deepa, Jaiswal2 deepajzsi@gmail.com, Madasamy, Karuthapandi2 kpandi83@gmail.com, Jadhav, Shrikant2 shrikantjadhavzsi@gmail.com, Kunte, Kalyani B.3 kalyanikunte18@gmail.com
Publikováno v:
Journal of Insect Biodiversity & Systematics. 2023, Vol. 9 Issue 3, p449-467. 19p.
Autor:
Gundavarapu, Saaketh Koundinya, Agarwal, Shreya, Arora, Arushi, Jagadeeshaiah, Chandana Thimmalapura
Machine unlearning, a novel area within artificial intelligence, focuses on addressing the challenge of selectively forgetting or reducing undesirable knowledge or behaviors in machine learning models, particularly in the context of large language mo
Externí odkaz:
http://arxiv.org/abs/2405.15152
We present SLIP (SAM+CLIP), an enhanced architecture for zero-shot object segmentation. SLIP combines the Segment Anything Model (SAM) \cite{kirillov2023segment} with the Contrastive Language-Image Pretraining (CLIP) \cite{radford2021learning}. By in
Externí odkaz:
http://arxiv.org/abs/2405.07284
Autor:
Hales, Thomas, Vajjha, Koundinya
This book uses optimal control theory to prove that the most unpackable centrally symmetric convex disk in the plane is a smoothed polygon. A smoothed polygon is a polygon whose corners have been rounded in a special way by arcs of hyperbolas. To be
Externí odkaz:
http://arxiv.org/abs/2405.04331
Akademický článek
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Autor:
Safavigerdini, Kaveh, Nouduri, Koundinya, Surya, Ramakrishna, Reinhard, Andrew, Quinlan, Zach, Bunyak, Filiz, Maschmann, Matthew R., Palaniappan, Kannappan
We present a pipeline for predicting mechanical properties of vertically-oriented carbon nanotube (CNT) forest images using a deep learning model for artificial intelligence (AI)-based materials discovery. Our approach incorporates an innovative data
Externí odkaz:
http://arxiv.org/abs/2307.07912
Autor:
Rakshita Sukruth Kolipakala, Suranjana Basu, Senjuti Sarkar, Beneta Merin Biju, Daniela Salazar, Likhit Reddy, Pushya Pradeep, Muniraj Krishnaveni Yuvapriya, Shrijita Nath, Riley Gall, Anish Hemanth Samprathi, Harshitha Balaji, Eeshaan A. B. Koundinya, Aparna Shetye, Deepesh Nagarajan
Publikováno v:
ACS Omega, Vol 9, Iss 34, Pp 36353-36370 (2024)
Externí odkaz:
https://doaj.org/article/9beed1c300aa4d0c9e17e8f48ac6c595
Autor:
Natalia Pinzón, Vikram Koundinya, Ryan E. Galt, William O'R. Dowling, Marcela Baukloh, Namah C. Taku-Forchu, Tracy Schohr, Leslie M. Roche, Samuel Ikendi, Mark Cooper, Lauren E. Parker, Tapan B. Pathak
Publikováno v:
Frontiers in Research Metrics and Analytics, Vol 9 (2024)
The proliferation of AI-powered bots and sophisticated fraudsters poses a significant threat to the integrity of scientific studies reliant on online surveys across diverse disciplines, including health, social, environmental and political sciences.
Externí odkaz:
https://doaj.org/article/5f8bdfb882a84db7b92015733c29ffdd
Publikováno v:
Tropical Plant Research. 7:427-439
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8288aa31adb27c099d21cd714f6f2486
https://doi.org/10.22271/tpr.2020.v7.i2.051
https://doi.org/10.22271/tpr.2020.v7.i2.051