A handwritten character model training method, a handwritten character recognition method, an apparatus, a device, and a medium. The handwritten character model training method comprises: acquiring a standard Chinese character training sample, labeling the standard Chinese character training sample and obtaining the real result of each sample, performing model training according to the real result of each sample, and using a batch gradient descent-based time-dependent reverse propagation algorithm to update network parameters of a bidirectional long short-term memory neural network, so as to acquire a standard Chinese character recognition model; acquiring and using a non-standard Chinese character training sample, to train and acquire an adjusted handwritten Chinese character recognition model; acquiring and using a Chinese character sample to be tested to obtain an erroneous character training sample; and using the erroneous character training sample to update the network parameters of the handwritten Chinese character recognition model, to acquire a target handwritten Chinese character recognition model. With the handwritten character model training method, a target handwritten Chinese character recognition model having a high handwritten character recognition rate can be obtained.
HANDWRITTEN CHARACTER MODEL TRAINING METHOD, HANDWRITTEN CHARACTER RECOGNITION METHOD, APPARATUS, DEVICE, AND MEDIUM