Vehicle detection in aerial imagery has become tremendously a challenging task due to the
low resolution characteristics of the aerial images. Super-Resolution; a technique which …

In this paper, we propose a novel attribute-guided cross-resolution (low-resolution to high-
resolution) face recognition framework that leverages a coupled generative adversarial …

In this paper, we present a novel architecture that integrates a deep hashing framework with
a neural network decoder (NND) for application to face template protection. It improves upon …

In this paper, we propose a novel multimodal deep hashing neural decoder (MDHND)
architecture, which integrates a deep hashing framework with a neural network decoder …

As multimedia technology has advanced in recent years, the use of enormous image
libraries has dramatically expanded. In applications for image processing, image retrieval …

Hyperspectral imaging systems collect and process information from specific wavelengths
across the electromagnetic spectrum. The fusion of multi-spectral bands in the visible …

Target detection systems identify targets by localizing their coordinates on the input image of
interest. This is ideally achieved by labeling each pixel in an image as a background or a …

Deep neural networks have presented impressive performance in biometric applications.
However, their performance is highly at risk when facing carefully crafted input samples …

The great success of Convolutional Neural Networks (CNN) for facial attribute prediction
relies on a large amount of labeled images. Facial image datasets are usually annotated by …

In this paper, we address the problem of face hallucination by proposing a novel multi-scale
generative adversarial network (GAN) architecture optimized for face verification. First, we …