Stochastic Markov $k$-Tree Network Sparsification Learning for Image Classification
Zhiming Wang, Xia Zhang · 2022 4th International Conference on Communications, Information System and Computer Engineering (CISCE) · 2022
Classification in computer science is for the purpose of designing and implementing an algorithmic classifier to identify the target category given by an observed data, which has played a key role within the recent decades. The author, in this paper, proposed a novel image classification learning method associated with machine learning by introducing network sparsification modelling algorithm based on stochastic Markov k-tree graph learning. The proposed Markov k-tree network sparsification learning demonstrated its overall state-of-art performance, as our testing and analysis proved, on multiple datasets which are generally well-used for the image classification application.