Zhongming Jin

Learn More
Recently, hashing techniques have been widely applied to solve the approximate nearest neighbors search problem in many vision applications. Generally, these hashing approaches generate 2^c buckets, where c is the length of the hash code. A good hashing method should satisfy the following two requirements: 1) mapping the nearby data points into the same(More)
Cross media retrieval engines have gained massive popularity with rapid development of the Internet. Users may perform queries in a corpus consisting of audio, video, and textual information. To make such systems practically possible for large mount of multimedia data, two critical issues must be carefully considered: (a) reduce the storage as much as(More)
In many real world scenarios, active learning methods are used to select the most informative points for labeling to reduce the expensive human action. One direction for active learning is selecting the most representative points, ie., selecting the points that other points can be approximated by linear combination of the selected points. However, these(More)
Edge-loading generates higher wear rates in ceramic-on-ceramic total hip prosthesis (THP). To investigate the friction coefficient (FC) in these conditions, three alumina ceramic (Biolox Forte) 32 mm-diameter components were tested using a hip friction simulator. The cup was positioned with a 75 degrees abduction angle to achieve edge-loading conditions.(More)
An effective lubrication can significantly reduce wear of metal-on-metal artificial hip joints. The improvement of the lubrication can be achieved through the optimisation of the bearing geometry in terms of a small clearance and/or the structural support such as a polyethylene backing underneath a metallic bearing in a sandwich acetabular cup form. The(More)
Nowadays, Nearest Neighbor Search becomes more and more important when facing the challenge of big data. Traditionally, to solve this problem, researchers mainly focus on building effective data structures such as hierarchical k-means tree or using hashing methods to accelerate the query process. In this paper, we propose a novel unified approximate nearest(More)
Recently, the hashing techniques have been widely applied to approximate the nearest neighbor search problem in many real applications. The basic idea of these approaches is to generate binary codes for data points which can preserve the similarity between any two of them. Given a query, instead of performing a linear scan of the entire data base, the(More)
Person re-identification (re-ID), which aims at spotting a person of interest across multiple camera views, has gained more and more attention in computer vision community. In this paper, we propose a novel deep Siamese architecture based on convolutional neural network (CNN) and multi-level similarity perception. According to the distinct characteristics(More)
Fine-grained object retrieval, which aims at finding objects belonging to the same sub-category as the probe object from a large database, is becoming increasingly popular because of its research and application significance. Recently, convolutional neural network (CNN) based deep learning models have achieved promising retrieval performance, as they can(More)