Counting, locating, and sizing of shrimp larvae based on density map regression

Detection of surfacing white shrimp under hypoxia based on improved lightweight YOLOv5 model

(2023) Xun Ran et al.   AQUACULTURE INTERNATIONAL

Intensification of Penaeid Shrimp Culture: An Applied Review of Advances in Production Systems, Nutrition and Breeding

(2022) Maurício G. C. Emerenciano et al.   Animals

Research on fish bait particles counting model based on improved MCNN

(2022) Siyue Hou et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Automatic shrimp counting method using local images and lightweight YOLOv4

(2022) Lu Zhang et al.   BIOSYSTEMS ENGINEERING

A lightweight detection method for the spatial distribution of underwater fish school quantification in intensive aquaculture

(2022) Yingyi Chen et al.   AQUACULTURE INTERNATIONAL

LFCNet: A lightweight fish counting model based on density map regression

(2022) Yuanyang Zhao et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Shrimp egg counting with fully convolutional regression network and generative adversarial network

(2021) Junjie Zhang et al.   AQUACULTURAL ENGINEERING

Application of machine learning in intelligent fish aquaculture: A review

(2021) Shili Zhao et al.   AQUACULTURE

Portable Device for Ornamental Shrimp Counting Using Unsupervised Machine Learning

(2021) Chi-Tsai Yeh et al.   SENSORS AND MATERIALS

Evaluating the Effects of Different Processing Methods on the Nutritional Composition of Shrimp and the Antioxidant Activity of Shrimp Powder

(2021) Nora A. AlFaris et al.   SAUDI JOURNAL OF BIOLOGICAL SCIENCES

Deep learning for smart fish farming: applications, opportunities and challenges

(2020) Xinting Yang et al.   Reviews in Aquaculture

Automatic counting methods in aquaculture: A review

(2020) Daoliang Li et al.   JOURNAL OF THE WORLD AQUACULTURE SOCIETY

A computer vision system for oocyte counting using images captured by smartphone

(2019) Celso Soares Costa et al.   AQUACULTURAL ENGINEERING

Automatic live fingerlings counting using computer vision

(2019) Pedro Lucas França Albuquerque et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

U-Net: deep learning for cell counting, detection, and morphometry

(2018) Thorsten Falk et al.   NATURE METHODS

Automatic inspection machine for maize kernels based on deep convolutional neural networks

(2018) Chao Ni et al.   BIOSYSTEMS ENGINEERING

An automatic counting system for transparent pelagic fish eggs based on computer vision

(2015) Yane Duan et al.   AQUACULTURAL ENGINEERING