Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Shyam Prasad Adhikari"'
Publikováno v:
Frontiers in Plant Science, Vol 10 (2019)
Weeds in agricultural farms are aggressive growers which compete for nutrition and other resources with the crop and reduce production. The increasing use of chemicals to control them has inadvertent consequences to the human health and the environme
Externí odkaz:
https://doaj.org/article/10851e8597634778964d50763ab35e6b
Publikováno v:
International Journal of Molecular Sciences, Vol 20, Iss 7, p 1725 (2019)
Cell cytotoxicity assays, such as cell viability and lactate dehydrogenase (LDH) activity assays, play an important role in toxicological studies of pharmaceutical compounds. However, precise modeling for cytotoxicity studies is essential for success
Externí odkaz:
https://doaj.org/article/f697518d3beb4143933d76b89a6289ef
Publikováno v:
Sensors, Vol 11, Iss 4, Pp 4372-4384 (2011)
This paper proposes an extension of the weak classifiers derived from the Haar-like features for their use in the Viola-Jones object detection system. These weak classifiers differ from the traditional single threshold ones, in that no specific thres
Externí odkaz:
https://doaj.org/article/838e3ce9cc6d4369bf3b712be74787ca
Publikováno v:
Sensors, Vol 18, Iss 1, p 178 (2018)
This paper presents a vision sensor-based solution to the challenging problem of detecting and following trails in highly unstructured natural environments like forests, rural areas and mountains, using a combination of a deep neural network and dyna
Externí odkaz:
https://doaj.org/article/6e276d9ad93846e2bdbf63d112a54105
Publikováno v:
Sensors, Vol 17, Iss 1, p 16 (2016)
A hybrid learning method of a software-based backpropagation learning and a hardware-based RWC learning is proposed for the development of circuit-based neural networks. The backpropagation is known as one of the most efficient learning algorithms. A
Externí odkaz:
https://doaj.org/article/aaa6ecea829d4ec38aefe1627b0489fa
Publikováno v:
Computer Vision and Machine Intelligence ISBN: 9789811978661
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3cb64d0ed2bcc552b84be892bafb2947
https://doi.org/10.1007/978-981-19-7867-8_26
https://doi.org/10.1007/978-981-19-7867-8_26
Autor:
Eun Joo Lee, Byung-Cheol Kang, Shyam Prasad Adhikari, Suk-Ja Yoon, Sang-Ah Lee, Jae-Seo Lee, Hyongsuk Kim, Byung-Ju Park
Publikováno v:
The Korean Journal of Oral and Maxillofacial Pathology. 45:59-65
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a83d303d66956d330c072b3e6aa61ebe
https://doi.org/10.17779/kaomp.2021.45.2.003
https://doi.org/10.17779/kaomp.2021.45.2.003
Publikováno v:
Nonlinear Dynamics. 99:3169-3196
This paper presents an in-depth and rigorous mathematical analysis of a family of nonlinear dynamical circuits whose only nonlinear component is a Chua Corsage Memristor (CCM) characterized by an explicit seven-segment piecewise-linear equation. When
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af8adc46c136d191913a2f51f8495725
https://doi.org/10.1007/s11071-020-05476-y
https://doi.org/10.1007/s11071-020-05476-y
Publikováno v:
IEEE Access, Vol 8, Pp 71272-71278 (2020)
This paper presents a novel vision based approach for detecting rows of crop in paddy field. The precise detection of crop row enables a farm-tractor to autonomously navigate the field for successful inter-row weeding. While prior works on crop row d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b8912ec6f4a09873dd1ad3f16bf7a23
https://doi.org/10.1109/access.2020.2987642
https://doi.org/10.1109/access.2020.2987642
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers. 66:3906-3916
Nonlinear memristor-based neural network and a circuit-based learning system is addressed in this work. The weights of the neural network are based on the memristor bridge synapse and the learning architecture is designed in analog–digital mixed ci
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffcfb9c7e4e6feda266c89fe72959f7a
https://doi.org/10.1109/tcsi.2019.2914125
https://doi.org/10.1109/tcsi.2019.2914125