State-of-the-art object detection networks depend on region proposal algorithms to
hypothesize object locations. Advances like SPPnet [1] and Fast R-CNN [2] have reduced …

In the context of fine-grained visual categorization, the ability to interpret models as human-
understandable visual manuals is sometimes as important as achieving high classification …

Object skeleton is a useful cue for object detection, complementary to the object contour, as
it provides a structural representation to describe the relationship among object parts. While …

With the advent of Deep Learning, the machine learning systems are able to recognize and
classify objects of interest in an image. Various advancement has been done in the field of …

In this paper, we study the task of detecting semantic parts of an object, eg, a wheel of a car,
under partial occlusion. We propose that all models should be trained without seeing …

Several unmanned retail stores have been introduced with the development of sensors,
wireless communication, and computer vision technologies. A vision-based kiosk that is only …

This paper proposes an edge-technology based feedback system for the visually impaired
people in a form of smart glasses. The glasses contain a microcomputer attached with a …

Bird detection in LR images is essential for the applications of unmanned aerial vehicles. It
is still a challenging task because traditional discriminative features in high-resolution (HR) …

Widely used surveillance cameras have promoted large amounts of street scene data, which
contains one important but long-neglected object: the vehicle. Here we focus on the …

Object detection in synthetic aperture radar (SAR) imagery is a fundamental and challenging
problem in the field of SAR imagery analysis for many fields like military, intelligence …