Deep Residual Networks have recently been shown to significantly improve the
performance of neural networks trained on ImageNet, with results beating all previous …

With the development of Internet technology and the popularity of digital devices, Content-
Based Image Retrieval (CBIR) has been quickly developed and applied in various fields …

Computer-aided diagnosis of retinopathy is a research hotspot in the field of medical image
classification. Diabetic macular edema (DME) and age-related macular degeneration (AMD) …

Traditional operations, eg graph edit distance (GED), are no longer suitable for processing
the massive quantities of graph-structured data now available, due to their irregular …

Since convolutional neural network (CNN) can only extract local features, and long short-
term memory (LSTM) neural network model has a large number of learning calculations, a …

Deep hashing methods utilize an end-to-end framework to mutually learn feature
representations and hash codes, thereby achieving a better retrieval performance …

The purpose of this work is to quickly find useful information from the massive image
database in view of the images, videos, and other multimedia data generated on Internet …

Nowadays, visual object tracking becomes a hotspot and difficulty to achieve a real-time and
accurate target tracking, but the Siamese network has solved these difficulties because of its …

Despite the rapid strides in content-based image retrieval, a notable disparity persists
between the visual features of images and the semantic features discerned by humans …

In the study, the authors consider neural network-based classification methods for the actual
task of recognizing photo car numbers from a camera. Various types of neural network are …