Data is the driving force of machine learning, with the amount and quality of training data
often being more important for the performance of a system than architecture and training …

Abstract Deep Convolutional Neural Networks have been adopted for salient object
detection and achieved the state-of-the-art performance. Most of the previous works …

Although deep models have greatly improved the accuracy and robustness of image
segmentation, obtaining segmentation results with highly accurate boundaries and fine …

As a fundamental building block in computer vision, edges can be categorised into four
types according to the discontinuity in surface-Reflectance, Illumination, surface-Normal or …

With constant research in the last decade, Object Detection has become one of the rapidly
evolving sub-fields of Deep Learning. As a result, the complexity and applications of Object …

Power line detection plays an important role in an automated UAV-based electricity
inspection system, which is crucial for real-time motion planning and navigation along power …

Recently, deep learning-based methods, especially utilizing fully convolutional neural
networks, have shown extraordinary performance in salient object detection. Despite its …

Abstract Recently, Salient Object Detection (SOD) has achieved promising results thanks to
the rapid evolution of CNN architectures. However, those CNN-based methods show limited …

With the advancement of computer vision, artificial intelligence, and remote sensing
technologies, deep learning algorithms are increasingly used in terrestrial, airborne, and …

Deep learning requires large amounts of annotated data. Manual annotation of objects in
video is, regardless of annotation type, a tedious and time-consuming process. In particular …