… image classification model, the dual-level convolutional … classification effect. Experiments
on three real hyperspectral datasets show that the dual-level convolutional neural network …

… (2) Research on Braille image recognition based on CRNN In this paper, a Braille image
recognition model based on convolutional neural network and recurrent neural network is …

… Through training with a large amount of ship image data, … target recognition based on
convolution neural network model is … image noise reduction, and the proposed convolution neural …

… We introduce a deep convolutional neural network (CNN) to … accuracy using patches
segmented from microscopic images … of convolutional neural networks in image classification In …

… Abstract: In recent years, neural network technology has developed rapidly and reached a …
human recognition in the field of image recognition. Traditional convolutional neural networks …

… By selecting the parameters of the convolutional neural network, CNN can be used to
maximize the advantages of high-resolution remote sensing image classification, make full use of …

… By constructing structured deep neural network architecture, physics-informed neural networks
(PINN) can be trained to solve supervised learning tasks with limited amount of boundary …