The key to solving fine-grained image categorization is finding discriminate and local
regions that correspond to subtle visual traits. Great strides have been made, with complex …

The study of flower classification system is a very important subject in the field of Botany. A
classifier of flowers with high accuracy will also bring a lot of fun to people's lives. However …

Recent results indicate that the generic descriptors extracted from the convolutional neural
networks are very powerful. This paper adds to the mounting evidence that this is indeed the …

Semantic part localization can facilitate fine-grained categorization by explicitly isolating
subtle appearance differences associated with specific object parts. Methods for pose …

Fine-grained image classification is to recognize hundreds of subcategories belonging to
the same basic-level category, such as 200 subcategories belonging to the bird, which is …

We introduce tools and methodologies to collect high quality, large scale fine-grained
computer vision datasets using citizen scientists--crowd annotators who are passionate and …

We propose an architecture for fine-grained visual categorization that approaches expert
human performance in the classification of bird species. Our architecture first computes an …

We present a state-of-the-art image recognition system, Deep Image, developed using end-
to-end deep learning. The key components are a custom-built supercomputer dedicated to …

Part models of object categories are essential for challenging recognition tasks, where
differences in categories are subtle and only reflected in appearances of small parts of the …

We propose a fine-grained recognition system that incorporates part localization, alignment,
and classification in one deep neural network. This is a nontrivial process, as the input to the …