Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Fateme Fotouhi"'
Autor:
Asheesh K. Singh, Behzad J. Balabaygloo, Barituka Bekee, Samuel W. Blair, Suzanne Fey, Fateme Fotouhi, Ashish Gupta, Amit Jha, Jorge C. Martinez-Palomares, Kevin Menke, Aaron Prestholt, Vishesh K. Tanwar, Xu Tao, Anusha Vangala, Matthew E. Carroll, Sajal K. Das, Guilherme DePaula, Peter Kyveryga, Soumik Sarkar, Michelle Segovia, Simone Silvestri, Corinne Valdivia
Publikováno v:
Frontiers in Agronomy, Vol 6 (2024)
To meet the grand challenges of agricultural production including climate change impacts on crop production, a tight integration of social science, technology and agriculture experts including farmers are needed. Rapid advances in information and com
Externí odkaz:
https://doaj.org/article/079a0657dce440258b2b8929a161081f
Autor:
Nagasubramanian, Koushik, Jubery, Talukder Z., Ardakani, Fateme Fotouhi, Mirnezami, Seyed Vahid, Singh, Asheesh K., Singh, Arti, Sarkar, Soumik, Ganapathysubramanian, Baskar
Deep learning models have been successfully deployed for a diverse array of image-based plant phenotyping applications including disease detection and classification. However, successful deployment of supervised deep learning models requires large am
Externí odkaz:
http://arxiv.org/abs/2006.04255
Autor:
Ashlyn Rairdin, Fateme Fotouhi, Jiaoping Zhang, Daren S. Mueller, Baskar Ganapathysubramanian, Asheesh K. Singh, Somak Dutta, Soumik Sarkar, Arti Singh
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
Using a reliable and accurate method to phenotype disease incidence and severity is essential to unravel the complex genetic architecture of disease resistance in plants, and to develop disease resistant cultivars. Genome-wide association studies (GW
Externí odkaz:
https://doaj.org/article/069e944f59ec48798ddd2308075ba99d
Publikováno v:
Frontiers in Robotics and AI, Vol 9 (2022)
In this paper we propose a new framework—MoViLan (Modular Vision and Language) for execution of visually grounded natural language instructions for day to day indoor household tasks. While several data-driven, end-to-end learning frameworks have be
Externí odkaz:
https://doaj.org/article/8008add58aab4f31a86beaf1279bb5ca
Autor:
Koushik Nagasubramanian, Talukder Jubery, Fateme Fotouhi Ardakani, Seyed Vahid Mirnezami, Asheesh K Singh, Arti Singh, Soumik Sarkar, Baskar Ganapathysubramanian
Publikováno v:
Plant Phenome Journal, Vol 4, Iss 1, Pp n/a-n/a (2021)
Abstract Deep learning models have been successfully deployed for a diverse array of image‐based plant phenotyping applications including disease detection and classification. However, successful deployment of supervised deep learning models requir
Externí odkaz:
https://doaj.org/article/1ce4128f51e34cfa91aaea434685c8f2
Publikováno v:
ETRI Journal, Vol 40, Iss 5, Pp 653-663 (2018)
Patients with spinal cord injuries cannot move their limbs using their intact muscles. A suitable controller can be used to move their arms by employing the functional electrical stimulation method. In this article, a fuzzy exponential sliding‐mode
Externí odkaz:
https://doaj.org/article/02bf2004487b485f98053b86d4841c48
Autor:
Ashlyn Rairdin, Fateme Fotouhi, Jiaoping Zhang, Daren S Mueller, Baskar Ganapathysubramanian, Asheesh K Singh, Somak Dutta, Soumik Sarkar, Arti Singh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3a3d4d634de579516b36e88cdb9d5b4f
https://doi.org/10.22541/au.166497104.42473667/v1
https://doi.org/10.22541/au.166497104.42473667/v1
Autor:
Arti Singh, Talukder Z. Jubery, Asheesh K. Singh, Baskar Ganapathysubramanian, Seyed Vahid Mirnezami, Koushik Nagasubramanian, Fateme Fotouhi Ardakani, Soumik Sarkar
Publikováno v:
Plant Phenome Journal, Vol 4, Iss 1, Pp n/a-n/a (2021)
Deep learning models have been successfully deployed for a diverse array of image‐based plant phenotyping applications including disease detection and classification. However, successful deployment of supervised deep learning models requires large
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88cee0aa0b704df0ad023ff5eb139538
https://doaj.org/article/1ce4128f51e34cfa91aaea434685c8f2
https://doaj.org/article/1ce4128f51e34cfa91aaea434685c8f2
Autor:
Javad Norouzi Nia, Atousa Zarindast, Masoud Salehi, Fateme Fotouhi, Mahdi Moqri, Nima Safaei, Reyhaneh Bijari, Atefeh Rajabalizadeh, Mojtaba Talafidaryani
The monitoring of severely ill patients is a crucial procedure for every intensive care unit (ICU). By applying different data exploration methods on monitoring data, some perspective can be gained. In the present research, such monitoring data were
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b491f399e550b033cd7263df0be9bf3
https://doi.org/10.1101/2020.03.29.20042028
https://doi.org/10.1101/2020.03.29.20042028