The identification of the working stage is of great significance in the study of energy saving of excavators. In this paper, computer vision is introduced into the excavator's work cycle stage recognition, and the YoloV2 algorithm is used to establish a deep vision target detector to locate ...
yolo_v4 26. yolo_v4_tiny format_version: 3.0 toolkit_version: 5.0.0 published_date: 05/31/2023 The container name associated with the task can be derived as $DOCKER_REGISTRY/$DOCKER_NAME:$DOCKER_TAG. For example, from the log above, the Docker name to run detectnet_v2 can be derived...
Finally, the algorithm is used to fit the crop row and determine the omission locations. The specific objectives of this study are as follows. First, we propose an uncrewed rice transplanter omission detection method. Second, we design a CNN (YOLOv5-AC, YOLOv5 combines atrous spatial pyramid ...
System information (version) OpenCV => 4.1.2 Operating System / Platform => Windows 64 Bit Compiler => Visual Studio 2017 Cuda => 10.2 Hello ! I use darknet Yolo for object detection and it works very well. Unfortunately with the CPU it'...
Research on task path planning method for substation inspection robot and UAV based on genetic algorithm Based on the inspection environment and tasks of substation inspection robots and drones, a grid method is proposed to simulate the division of three-dimen... Wenjie Zheng,Yong Li,Sun Li,.....
To address the challenges associated with supervising workers who wear safety belts while working at heights, this study proposes a solution involving the utilization of an object detection model to replace manual supervision. A novel object detection model, named ESE-YOLOv8, is introduced...
To accomplish this, our paper discusses hardware and software components of a self driving car that includes usage of technologies such as Deep learning techniques namely Convolution Neural Networks, YOLO algorithm, Hough Transform Algorithms, Transfer Learning, Canny Edge Detection algorithm. Software ...
The identification of the working stage is of great significance in the study of energy saving of excavators. In this paper, computer vision is introduced into the excavator's work cycle stage recognition, and the YoloV2 algorithm is used to establish a deep vision target detector to locate ...
To ensure the safety of workers in automated factories, a novel and efficient warning-range algorithm is proposed to determine whether a person is in the warning range, introducing YOLOv4 tiny-object detection algorithms to improve the accuracy of determining objects. The results are displayed on ...
This innovative method involves, firstly, isolating the objects using a Convolutional Neutral Network (CNN), namely the Region-Based CNN (YOLOv8 Tiny) for recognising the objects (stage 1). Next, the Non-Maximum Suppression (NMS) algorithm was used for filtering the objects isolated in previous...