Alzayat Saleh developed a computer vision framework that can aid aquaculture experts in analyzing fish habitats. In particular, he developed a labelling efficient method of training a CNN-based fish-detector and also developed a model that estimates the fish weight directly from its image
[eng] In the last decade, deep learning has revolutionized almost every scientific discipline and e...
Use two different detection models and combine them with a tracking algorithm to be able to track fi...
Identifying and counting fish individuals on photos and videos is a crucial task to cost-effectively...
Marine scientists use remote underwater image and video recording to survey fish species in their na...
Marine ecosystems and their fish habitats are becoming increasingly important due to their integral ...
Abstract: Computer vision has been applied to fish recognition for at least three decades. With the ...
Underwater imagery processing is in high demand, but the unrestricted environment makes it difficult...
Visual analysis of complex fish habitats is an important step towards sustainable fisheries for huma...
Traditionally, there has not been extensive research in underwater datasets using Deep Learning. A k...
Underwater Fish Species Recognition (UFSR) has attained significance because of evolving research in...
Recently, human being’s curiosity has been expanded from the land to the sky and the sea. Besides se...
Deep neural networks have proven to be an effective method in classification of images. The ability ...
International audienceOne of the current challenges of marine ecology is to monitor biodiversity acc...
This study presents an application that employs a machine-learning algorithm to identify fish specie...
This thesis presents research on automated video analysis using computer vision systems, for analysi...
[eng] In the last decade, deep learning has revolutionized almost every scientific discipline and e...
Use two different detection models and combine them with a tracking algorithm to be able to track fi...
Identifying and counting fish individuals on photos and videos is a crucial task to cost-effectively...
Marine scientists use remote underwater image and video recording to survey fish species in their na...
Marine ecosystems and their fish habitats are becoming increasingly important due to their integral ...
Abstract: Computer vision has been applied to fish recognition for at least three decades. With the ...
Underwater imagery processing is in high demand, but the unrestricted environment makes it difficult...
Visual analysis of complex fish habitats is an important step towards sustainable fisheries for huma...
Traditionally, there has not been extensive research in underwater datasets using Deep Learning. A k...
Underwater Fish Species Recognition (UFSR) has attained significance because of evolving research in...
Recently, human being’s curiosity has been expanded from the land to the sky and the sea. Besides se...
Deep neural networks have proven to be an effective method in classification of images. The ability ...
International audienceOne of the current challenges of marine ecology is to monitor biodiversity acc...
This study presents an application that employs a machine-learning algorithm to identify fish specie...
This thesis presents research on automated video analysis using computer vision systems, for analysi...
[eng] In the last decade, deep learning has revolutionized almost every scientific discipline and e...
Use two different detection models and combine them with a tracking algorithm to be able to track fi...
Identifying and counting fish individuals on photos and videos is a crucial task to cost-effectively...
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