Reliably detecting objects in broad-area overhead or satellite images has become an
increasingly pressing need, as the capabilities for image acquisition are growing rapidly …

Researches in psychology, perception and related fields show that there may be a two-stage
process involved in human vision. In this paper, we propose an approach by following a two …

We present a prototype video tracking and person categorization system that uses face and
person soft biometric features to tag people while tracking them in multiple camera views …

This paper presents an extension of the HMAX model, a neural network model for image
classification. The HMAX model can be described as a four-level architecture, with the first …

The biologically inspired model (BIM) proposed by Serre presents a promising solution to
object categorization. It emulates the process of object recognition in primates' visual cortex …

Dealing with the curse of dimensionality is a key challenge in high-dimensional data
visualization. We present SeekAView to address three main gaps in the existing research …

In this work, we present a novel visual perception-inspired local description approach as a
preprocessing step for deep learning. With the ongoing growth of visual data, efficient image …

The superior performance of deep convolutional networks over high-dimensional problems
have made them very popular for several applications. Despite their wide adoption, their …

Effectively solving the problem of sketch generation, which aims to produce human-drawing-
like sketches from real photographs, opens the door for many vision applications such as …

It has been demonstrated by Serre et al. that the biologically inspired model (BIM) is effective
for object recognition. It outperforms many state-of-the-art methods in challenging …