Image Recognition of Mine Water Inrush Based on Bilinear Convolutional Neural Network with Few-Shot Learning.

With the increasingly widespread application of deep learning technology in the field of coal mines, the image recognition of mine water inrush has become a hot research topic. Underground environments are complex, and images have a high noise and low brightness. Additionally, mine water inrush is accidental, and few actual image samples are available. Therefore, this paper proposes an algorithm that recognizes mine water inrush images based on few-shot deep learning. According to the characteristics of images with coal wall water seepage, a bilinear neural network was used to extract the image features and enhance the network's fine-grained image recognition. First, features were extracted using a bilinear convolutional neural network. Second, the network was pre-trained based on cosine similarity. Finally, the network was fine-tuned for the predicted image. For single-line feature extraction, the method is compared with big data and few-shot learning. According to the experimental results, the recognition rate reaches 95.2% for few-shot learning based on a bilinear neural network, thus demonstrating its effectiveness.

Compensatory recombination phenomena of neurological functions in central dysphagia patients.

We speculate that cortical reactions evoked by swallowing activity may be abnormal in patients with central infarction with dysphagia. The present study aimed to detect functional imaging features of cerebral cortex in central dysphagia patients by using blood oxygen level-dependent functional magnetic resonance imaging techniques. The results showed that when normal controls swallowed, primary motor cortex (BA4), insula (BA13), premotor cortex (BA6/8), supramarginal gyrus (BA40), and anterior cingulate cortex (BA24/32) were activated, and that the size of the activated areas were larger in the left hemisphere compared with the right. In recurrent cerebral infarction patients with central dysphagia, BA4, BA13, BA40 and BA6/8 areas were activated, while the degree of activation in BA24/32 was decreased. Additionally, more areas were activated, including posterior cingulate cortex (BA23/31), visual association cortex (BA18/19), primary auditory cortex (BA41) and parahippocampal cortex (BA36). Somatosensory association cortex (BA7) and left cerebellum in patients with recurrent cerebral infarction with central dysphagia were also activated. Experimental findings suggest that the cerebral cortex has obvious hemisphere lateralization in response to swallowing, and patients with recurrent cerebral infarction with central dysphagia show compensatory recombination phenomena of neurological functions. In rehabilitative treatment, using the favorite food of patients can stimulate swallowing through visual, auditory, and other nerve conduction pathways, thus promoting compensatory recombination of the central cortex functions.