In the early days, content-based image retrieval (CBIR) was studied with global features.
Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively …

The content based image retrieval aims to find the similar images from a large scale dataset
against a query image. Generally, the similarity between the representative features of the …

This paper presents a simple yet effective supervised deep hash approach that constructs
binary hash codes from labeled data for large-scale image search. We assume that the …

The progress of brain cognition and learning mechanisms has provided new inspiration for
the next generation of artificial intelligence (AI) and provided the biological basis for the …

Image instance retrieval is the problem of retrieving images from a database which contain
the same object. Convolutional Neural Network (CNN) based descriptors are becoming the …

Artificial intelligence (AI) has been positioned as being the most important recent
advancement in radiology, if not the most potentially disruptive. Singapore radiologists have …

With the advances in both stable interest region detectors and robust and distinctive
descriptors, local feature-based image or object retrieval has become a popular research …

In addtion to security purposes, closed circuit video camera usually installed in a business
establishment can provide extra customer information, eg, a frequently visited area. Such …

In this work, we focus on the problem of image instance retrieval with deep descriptors
extracted from pruned Convolutional Neural Networks (CNN). The objective is to heavily …

This paper summarizes the feasibility of constructing the recommended reading system in
the library of high medical college, and analyzes the core technology‐recommendation …