Enhanced YOLOv5s-Based Algorithm for Industrial Part Detection.

In complex industrial environments, accurate recognition and localization of industrial targets are crucial. This study aims to improve the precision and accuracy of object detection in industrial scenarios by effectively fusing feature information at different scales and levels, and introducing edge detection head algorithms and attention mechanisms. We propose an improved YOLOv5-based algorithm for industrial object detection.

A Survey of 6DoF Object Pose Estimation Methods for Different Application Scenarios.

Recently, 6DoF object pose estimation has become increasingly important for a broad range of applications in the fields of virtual reality, augmented reality, autonomous driving, and robotic operations. This task involves extracting the target area from the input data and subsequently determining the position and orientation of the objects. In recent years, many new advances have been made in pose estimation.

Camellia nitidissima Chi flower extract alleviates obesity and related complications and modulates gut microbiota composition in rats with high-fat-diet-induced obesity.

Background: The aim of this study was to investigate the potential anti-obesity effects of Camellia nitidissima Chi flower extract (Cnfe) by examining its effects in terms of the regulation of lipid levels and modulation of gut microbiota in rats with high-fat-diet-induced obesity.

Results: Our results demonstrated that Cnfe significantly decreased weight gain by reducing appetite and decreasing high-fat food intake. Further, Cnfe restored normal lipid metabolism and improved insulin sensitivity and glucose tolerance in rats fed a high-fat diet.

Dual-NMS: A Method for Autonomously Removing False Detection Boxes from Aerial Image Object Detection Results.

In the field of aerial image object detection based on deep learning, it's difficult to extract features because the images are obtained from a top-down perspective. Therefore, there are numerous false detection boxes. The existing post-processing methods mainly remove overlapped detection boxes, but it's hard to eliminate false detection boxes.

Real-Time Large-Scale Dense Mapping with Surfels.

Real-time dense mapping systems have been developed since the birth of consumer RGB-D cameras. Currently, there are two commonly used models in dense mapping systems: truncated signed distance function (TSDF) and surfel. The state-of-the-art dense mapping systems usually work fine with small-sized regions.