The field of biometrics research encompasses the need to associate an identity to an
individual based on the persons physiological or behaviour traits. While the use of intrusive …

In this paper, we consider the problem of pedestrian detection in natural scenes. Intuitively,
instances of pedestrians with different spatial scales may exhibit dramatically different …

Abstract Convolutional Neural Network (CNN) based methods generally take crowd
counting as a regression task by outputting crowd densities. They learn the map** …

Pedestrian detection is an important but challenging problem in computer vision, especially
in human-centric tasks. Over the past decade, significant improvement has been witnessed …

Human detection and activity recognition is very important research area in the healthcare,
video surveillance, pedestrian detection, intelligent vehicle system and home care center …

In this paper, we propose an efficient algorithm to remove rain or snow from a single color
image. Our algorithm takes advantage of two popular techniques employed in image …

Network in network (NiN) is an effective instance and an important extension of deep
convolutional neural network consisting of alternating convolutional layers and pooling …

Despite the previous success of object analysis, detecting and segmenting a large number
of object categories with a long-tailed data distribution remains a challenging problem and is …

The activation functions play increasingly important roles in deep convolutional neural
networks. The traditional activation functions have some problems such as gradient …

Pedestrian detection based on the combination of convolutional neural network (CNN) and
traditional handcrafted features (ie, HOG+ LUV) has achieved great success. In general …