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Advancements towards selective barrier passage by automatic species identification: applications of deep convolutional neural networks on images of dewatered fish

机译：自动种类识别选择性障碍通道的进步：深卷积神经网络对脱水鱼图像的应用

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Jesse Eickholt; Dylan Kelly; Janine Bryan; Scott Miehls; Dan Zielinski;
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1. Advancements towards selective barrier passage by automatic species identification: applications of deep convolutional neural networks on images of dewatered fish [J] . Eickholt Jesse, Kelly Dylan, Bryan Janine, ICES Journal of Marine Science . 2020,第7a8期

机译：自动种类识别选择性障碍通道的进步：深卷积神经网络对脱水鱼图像的应用
2. Applications of deep convolutional neural networks to predict length, circumference, and weight from mostly dewatered images of fish [J] . Nicholas Bravata, Dylan Kelly, Jesse Eickholt, Ecology and Evolution . 2020,第17期

机译：深度卷积神经网络预测大多数脱水图像的长度，周长和重量的应用
3. Towards automatic wild animal monitoring: Identification of animal species in camera-trap images using very deep convolutional neural networks [J] . Alexander Gomez Villa, Augusto Salazar, Francisco Vargas Ecological informatics: an international journal on ecoinformatics and computational ecology . 2017,第期

机译：朝向自动野生动物监测：使用非常深的卷积神经网络识别相机 - 陷阱图像中的动物物种
4. Identifying species of common sea fish harvested by longliner using deep convolutional neural networks [C] . American Society of Agricultural and Biological Engineers Annual International Meeting . 2019

机译：使用深卷积神经网络识别由延绳子收获的常见海洋鱼类
5. Deep Learning Convolutional Neural Network Applications in Image Analysis to Identify Defects [D] . Umakanth, Srijith Parakkat 2018

机译：深度学习卷积神经网络在图像分析中识别缺陷的应用
6. Applications of deep convolutional neural networks to predict length circumference and weight from mostly dewatered images of fish [O] . Nicholas Bravata, Dylan Kelly, Jesse Eickholt, 2020

机译：深度卷积神经网络预测大多数脱水图像的长度周长和重量的应用
7. Applications of deep convolutional neural networks to predict length, circumference, and weight from mostly dewatered images of fish [O] . Nicholas Bravata, Dylan Kelly, Jesse Eickholt, 2020

机译：深度卷积神经网络预测大多数脱水图像的长度，周长和重量的应用

Advancements towards selective barrier passage by automatic species identification: applications of deep convolutional neural networks on images of dewatered fish

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