Object detection is one of the most fundamental and challenging tasks to locate objects in
images and videos. Over the past, it has gained much attention to do more research on …

In the last few years, deep learning has led to very good performance on a variety of
problems, such as visual recognition, speech recognition and natural language processing …

In image classification, visual separability between different object categories is highly
uneven, and some categories are more difficult to distinguish than others. Such difficult …

In this paper we study how to perform object classification in a principled way that exploits
the rich structure of real world labels. We develop a new model that allows encoding of …

There are different applications of computer vision and digital image processing in various
applied domains and automated production process. In textile industry, fabric defect …

Convolutional Neural Network (CNN) image classifiers are traditionally designed to have
sequential convolutional layers with a single output layer. This is based on the assumption …

Convolutional neural networks, in which each layer receives features from the previous layer
(s) and then aggregates/abstracts higher level features from them, are widely adopted for …

In recent years, image annotation has attracted extensive attention due to the explosive
growth of image data. With the capability of describing images at the semantic level, image …

Given a food image, can a fine-grained object recognition engine tell" which restaurant
which dish" the food belongs to? Such ultra-fine grained image recognition is the key for …

While machine learning approaches to visual emotion recognition offer great promise,
current methods consider training and testing models on small scale datasets covering …