Video occurrences and observation by category of brackish dataset.

<p>Video occurrences and observation by category of brackish dataset.</p>

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Bibliographic Details
Main Author:	Manimurugan S. (20314652) (author)
Other Authors:	Karthikeyan P. (20314655) (author), Narmatha C. (20314658) (author), Majed M. Aborokbah (20314661) (author), Anand Paul (19646164) (author), Subramaniam Ganesan (18173638) (author), Rajendran T. (20314664) (author), Mohammad Ammad-Uddin (20314667) (author)
Published:	2024
Subjects:	Microbiology Neuroscience Evolutionary Biology Inorganic Chemistry Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified vanishing gradient problem underwater object detection stress underwater environments star fish object sea resource development restricted boltzmann machine efficient underwater exploration effective feature learning big fish object architecture handles variable achieves enhanced significance proposed approach introduces processing sequences bidirectionally directional long short capturing complex patterns big fish 98 capturing long rbm approach length sequences xlink "> urpc dataset term memory term dependencies robust solution research addresses rbm ). model benefits imperative need hybrid model future contexts findings underscore enhance comprehension comprehensive evaluations challenges posed autonomous operations abstract representations
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