Application of deep learning in the detection and practical evaluation of ski resort teaching area

Abstract

SummaryThe teaching land of ski resorts provides learning sites for beginners of skiing. The teaching sites of different ski resorts are different. When selecting teaching scenes, we need to focus on the safety of the site. The focus of our research is to detect more suitable teaching land in the whole ski resort and evaluate its practical indicators. In order to accurately detect the teaching area in the snow field, we propose a method based on deep learning. The algorithm innovatively optimizes the convolution network. The experiment combines convolutional neural network with recurrent neural network for training, and uses the output of convolutional neural network to train recurrent neural network, so as to continuously predict the next optimal teaching area in the sequence. The purpose of training is to optimize the detection result area. The experimental results show that the model can better detect the sites suitable for teaching in the snow field.