Visual perception is critical and essential to understand phenomenon and environments of
the world. Pervasively configured devices like cameras are key in dynamic status …

As one of the primary computer vision problems, object detection aims to find and locate
semantic objects in digital images. Different with object classification, which only recognizes …

Recently real-time detection, and recognition of an object of interest are becoming vital tasks
in visual data processing and computer vision. Various models have been deployed to …

In recent years, convolutional neural networks have shown great success in various
computer vision tasks such as classification, object detection, and scene analysis. These …

The data of target detection in remote sensing images are diverse, and the detection results
of some categories with a small number of samples are poor. In order to solve this problem …

Real-time object detection using deep learning has emerged as a burgeoning field of study
due to its potential for a wide range of applications, including autonomous driving, robotics …

Object detection can be regarded as one of the most fundamental and challenging visual
recognition task in computer vision and it has received great attention over the past few …

This paper proposes a learnable line encoding technique for bounding boxes commonly
used in the object detection task. A bounding box is simply encoded using two main points …

Recent progress in deep learning has led to accurate and efficient generic object detection
networks. Training of highly reliable models depends on large datasets with highly textured …

Deep learning is a relatively new branch of machine learning in which computers are taught
to recognize patterns in massive volumes of data. It primarily describes learning at various …