Image Classification Based on Improved Unsupervised Clustering Algorithm
摘要
This paper proposes a k-means model based on density weighting, which is applied to the field of image classification and fused with deep neural network to train pseudo-labels. While clustering the learning features of the residual network, the network parameters are updated to achieve. The clustering performance of pseudo-labeled datasets is improved to solve the problem of scarcity of labeled data.