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International Journal of Food Properties Volume 20, 2017 - Issue sup2
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Original Articles

Computer vision based technique for identification of fish quality after pesticide exposure

Namita SengarDepartment of Electronics & Communication Engineering, Amity University, Noida, India
,
Malay Kishore DuttaDepartment of Electronics & Communication Engineering, Amity University, Noida, IndiaCorrespondence[email protected]
&
Biplab SarkarICAR - Indian Institute of Agricultural Biotechnology, Ranchi, Jharkhand, India
Pages 2192-2206 | Received 13 Feb 2017, Accepted 15 Aug 2017, Published online: 28 Dec 2017

Citations (6)

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Shubham Nimbkar, Manoj Auddy, Ishita Manoj & S Shanmugasundaram. (2023) Novel Techniques for Quality Evaluation of Fish: A Review. Food Reviews International 39:1, pages 639-662.
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Articles from other publishers (5)

J.M.V.D.B. Jayasundara, R.M.L.S. Ramanayake, H.M.N.B. Senarath, H.M.S.L. Herath, G.M.R.I. Godaliyadda, M.P.B. Ekanayake, H.M.V.R. Herath & S. Ariyawansa. (2023) Deep learning for automated fish grading. Journal of Agriculture and Food Research 14, pages 100711.
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Ritesh Maurya, Arti Srivastava, Ashutosh Srivastava, Vinay Kumar Pathak & Malay Kishore Dutta. (2023) Computer aided detection of mercury heavy metal intoxicated fish: an application of machine vision and artificial intelligence technique. Multimedia Tools and Applications 82:13, pages 20517-20536.
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Kadukothanahally Nagaraju Shivaprakash, Niraj Swami, Sagar Mysorekar, Roshni Arora, Aditya Gangadharan, Karishma Vohra, Madegowda Jadeyegowda & Joseph M. Kiesecker. (2022) Potential for Artificial Intelligence (AI) and Machine Learning (ML) Applications in Biodiversity Conservation, Managing Forests, and Related Services in India. Sustainability 14:12, pages 7154.
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Nikos Petrellis. (2021) Measurement of Fish Morphological Features through Image Processing and Deep Learning Techniques. Applied Sciences 11:10, pages 4416.
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Huu-Dung Do, Dong-Eon Kim, Minh Binh Lam & Wan-Young Chung. (2021) Self-Powered Food Assessment System Using LSTM Network and 915 MHz RF Energy Harvesting. IEEE Access 9, pages 97444-97456.
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