深層学習による水族館定点カメラ画像からの水の透明度判定

抄録

Aquariums have the task of water clarity testing for regular water exchange. Water clarity can indeed be detected by chemical reagents or special equipment, while the method is very tedious and complicated. Recently, artificial intelligence has been put to practical use in society, and it can contribute to the efficiency of water exchange using Deep Learning algorithms. In this research, we confirmed that water transparency can be determined using Convolutional Neural Networks, and that the water transparency determination achieved more correct answers better than the human eye. It was shown that a majority decision could improve the accuracy compared to classifying a single image.