Regional integrated energy system (RIES) plays an important role in the energy economy
because of its advantages such as low environmental pollution and high efficiency cascade …

Convolutional neural networks (CNNs) have achieved human-level performance in various
computer vision tasks, such as image classification, object detection & segmentation, etc …

Convolutional neural networks (CNNs), which have been the state-of-the-art in many image-
related applications, are prone to losing important spatial information between image …

Human pose estimation is one of the issues that have gained many benefits from using state-
of-the-art deep learning-based models. Human pose, hand and mesh estimation is a …

Technological advances enable the design of systems that interact more closely with
humans in a multitude of previously unsuspected fields. Martial arts are not outside the …

Abstract Human Pose Estimation (HPE) aims at retrieving the 3D position of human joints
from images or videos. We show that current 3D HPE methods suffer a lack of viewpoint …

Spatio-temporal wind speed prediction is of great significance to the grid-connected
operation of multiple wind farms in smart grid. This paper proposes a spatio-temporal wind …

Estimating 3D human poses from images is an ill-posed regression problem, which is
usually tackled by viewpoint-invariant convolutional neural networks (CNNs). Recently …

Human pose estimation is a core component in applications for which some level of human–
computer interaction is required, such as assistive robotics, ambient assisted living or the …

Abstract 3D pose estimation remains a challenging task since human poses exhibit high
ambiguity and multi-granularity. Traditional graph convolution networks (GCNs) accomplish …