Automatic fish population counting by artificial neural network
Automatic fish population counting by artificial neural network
复制标题
通过人工神经网络自动计算鱼群数量
DOI：
10.1016/0044-8486(95)00003-k
复制
发表时间：
1995
期刊：
影响因子：
4.5
通讯作者：
D. Pilgrim
中科院分区：
文献类型：
--
作者：
Paul F. Newbury;P. Culverhouse;D. Pilgrim
提出了一种利用人工神经网络进行鱼群自动计数的新方法。训练了误差前馈反向传播神经网络，用于人工鱼种群的统计。训练后的网络随后被证明可以很好地概括以前看不见的鱼缸场景，在包含多达100条鱼的各种方向和重叠的场景中，成功率为94%。这优于像素计数和能量估计方法。
A new method of automatically counting fish using an artificial neural network is presented. A back propagation of error feed-forward neural network has been trained to count synthetic fish populations. Trained networks are subsequently shown to generalise well to previously unseen fish tank scenes, giving a 94% success rate on scenes containing up to 100 fish in a variety of orientations and overlaps. This out-performs both pixel counting and energy estimation methods.