World Journal of Engineering and Technology

World Journal of Engineering and Technology

ISSN Print: 2331-4222
ISSN Online: 2331-4249
www.scirp.org/journal/wjet
E-mail: wjet@scirp.org
"Estimating Mass of Harvested Asian Seabass Lates calcarifer from Images"
written by Dmitry A. Konovalov, Alzayat Saleh, Jose A. Domingos, Ronald D. White, Dean R. Jerry,
published by World Journal of Engineering and Technology, Vol.6 No.3B, 2018
has been cited by the following article(s):
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[4] A Review on Observer Assistance Systems for Harvested and Protected Fish Species
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[6] Accurate Segmentation of Tilapia Fish Body Parts Based on Deeplabv3+ for Advancing Phenotyping Applications
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[11] Modern Systems for Non-contact Fish Weighing. Review
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[13] Using unmanned aerial vehicle (UAV) with machine vision systems (MVS) to assess fish weight of red tilapia in river cage culture
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[14] High-throughput phenotyping by deep learning to include body shape in the breeding program of pacu (Piaractus mesopotamicus)
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[15] Coating Defects of Lithium-Ion Battery Electrodes and Their Inline Detection and Tracking
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[16] Unsupervised Fish Trajectory Tracking and Segmentation
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[17] Deep convolutional neural networks with transfer learning for estimation of Nile Tilapia mass
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[18] Weight and color evaluation of whole and filleted carp by image analysis
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[19] Image Analysis to Determine Length-Weight and Area-Weight Relationships, and Color Differences in Scaled Carp and Mirror Carp Grown in Fiberglass and Concrete …
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[20] Approach to glaucoma diagnosis and prediction based on multiparameter neural network
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[21] Applications of deep learning in fish habitat monitoring: A tutorial and survey
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[22] A Review on the Use of Computer Vision and Artificial Intelligence for Fish Recognition, Monitoring, and Management
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[23] Transformer-based Self-Supervised Fish Segmentation in Underwater Videos
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[24] Estimation of Physical Properties of Objects using Vision
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[25] Weight Estimation of Asian Sea Bass (Lates calcarifer) Comparing Whole Body with and without Fins using Computer Vision Technique
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[26] Weakly Supervised Underwater Fish Segmentation Using Affinity LCFCN
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[27] Evaluation of body weight and color of cultured European catfish (Silurus glanis) and African catfish (Clarias gariepinus) using image analysis
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[28] Computer Vision Estimation of Physical Parameters and Its Application to Power Requirements of Natural and Artificial Swimmers
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[29] Automatic contactless weighing of fish during experiments
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[30] Developing deep learning methods for aquaculture applications
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[31] A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis
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[32] Affinity LCFCN: Learning to Segment Fish with Weak Supervision
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[33] Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia
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[34] Automatic Weight Estimation of Harvested Fish from Images
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