For years, the YOLO series has been the de facto industry-level standard for efficient object
detection. The YOLO community has prospered overwhelmingly to enrich its use in a …

This paper presents a system for detecting damages in concrete dams that combines the
proposed YOLOv5s-HSC algorithm and a three-dimensional (3D) photogrammetric …

Compared with natural images, remote sensing targets have small and dense target shapes
as well as complex target backgrounds. As a result, insufficient detection accuracy and …

Recent studies have demonstrated that existing deep neural networks (DNNs) on 3D point
clouds are vulnerable to adversarial examples, especially under the white-box settings …

Oriented object detection (OOD) aims to precisely detect the objects with arbitrary orientation
in remote sensing images (RSIs). Up to now, most of the bounding box regression (BBR) …

Improving the detection accuracy and speed for small and multi-object detection is a hot
issue in traffic environments. Despite the substantial advances in object detection algorithms …

Abstract Nowadays, Unmanned Aerial Vehicles (UAVs) have become useful for various civil
applications, such as traffic monitoring and smart parkings, where real-time vehicle detection …

Accurate detection and counting of unopened cotton bolls at the early stage of cotton
maturation is an effective way to develop crop load management and harvesting strategies …

For the propose of improving the economic benefits of wind turbine utilization, an image
recognition model based on deep learning called 'Multivariate Information You Only Look …

Continual learning is an intellectual ability of artificial agents to learn new streaming labels
from sequential data. The main impediment to continual learning is catastrophic forgetting, a …