The invention provides a tree network method for testing and updating through WordNet embedding and relates to the intelligent classification of pictures. The method comprises a step of building a tree network, a step of carrying out pre-training, a step of carrying out dynamic pruning based on an SVM, dynamically pruning a node with a too low activation value of characteristic mapping and a subtree of the node in a test process, wherein if the activation value of the node is too low, the probability of a class represented by the node is low, so the probability of a descendant node is low andnegligible, a step of carrying out the acceleration of a model in the test process of using the SVM since the sum of the activation values of characteristic maps has strong linear separability, anda step of carrying out online update based on a branch and transmitting a sample with a high prediction probability back to the tree network for training with a detected image as a training sample.