We address the vehicle detection and classification problems using Deep Neural Networks
(DNNs) approaches. Here we answer to questions that are specific to our application …

In this paper, we propose a simple but effective semantic part-based weighting aggregation
(PWA) for image retrieval. The proposed PWA utilizes the discriminative filters of deep …

Visual search and image retrieval underpin numerous applications, however the task is still
challenging predominantly due to the variability of object appearance and ever increasing …

Convolutional Neural Network (CNN) is a very powerful approach to extract discriminative
local descriptors for effective image search. Recent work adopts fine-tuned strategies to …

In this paper, we propose a simple but effective semantic-based aggregation (SBA) method.
The proposed SBA utilizes the discriminative filters of deep convolutional layers as semantic …

High-efficiency compression of visual feature descriptors has recently emerged as an active
topic due to the rapidly increasing demand in mobile visual retrieval over bandwidth-limited …

For image retrieval methods based on bag of visual words, much attention has been paid to
enhancing the discriminative powers of the local features. Although retrieved images are …

Despite being highly secure, vein recognition suffers from the high inter-class similarity and
intra-class variation resulting from the uncontrolled image capture, making the design of …

In most state-of-the-art hashing-based visual search systems, local image descriptors of an
image are first aggregated as a single feature vector. This feature vector is then subjected to …

In the large-scale image retrieval task, the two most important requirements are the
discriminability of image representations and the efficiency in computation and storage of …