|
|
|
|
|
Zhuo Wang, Haojie Chen, Hongde Qin and Qin Chen
In the computer vision field, underwater object detection has been a challenging task. Due to the attenuation of light in a medium and the scattering of light by suspended particles in water, underwater optical images often face the problems of color dis...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chuandong Zhang, Huali Ding, Qinfeng Shi and Yunfei Wang
Due to differences in planting environment, color, shape, size, and compactness, accurate detection of grape clusters is very difficult. Herein, a real-time detection method for grape clusters based on the YOLOv5s deep learning algorithm was proposed. Mo...
ver más
|
|
|
|
|
|
|
|
|
|
|
Han Liang and Suyoung Seo
The system proposed in this paper provides a new idea for the recognition algorithm of road environments in safety-assisted driving systems, and subsequently improves the existing algorithm to reduce the computational cost and improve accuracy.
|
|
|
|
|
|
|
|
|
|
|
Changhong Liu, Jiawen Wen, Jinshan Huang, Weiren Lin, Bochun Wu, Ning Xie and Tao Zou
Underwater object detection is crucial in marine exploration, presenting a challenging problem in computer vision due to factors like light attenuation, scattering, and background interference. Existing underwater object detection models face challenges ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhikai Jiang, Li Su and Yuxin Sun
Accurate ship object detection ensures navigation safety and effective maritime traffic management. Existing ship target detection models often have the problem of missed detection in complex marine environments, and it is hard to achieve high accuracy a...
ver más
|
|
|
|
|
|
|
|
|
|
|
Fei Wu, Yitao Zhang, Lang Wang, Qiu Hu, Shengli Fan and Weiming Cai
The species and population size of marine fish are important for maintaining the ecological environment and reflecting climate change. Traditional fish detection methods mainly rely on manual or traditional computer vision, which has disadvantages such a...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jing Wang, Qianqian Li, Zhiqiang Fang, Xianglong Zhou, Zhiwei Tang, Yanling Han and Zhenling Ma
The rapid development of convolutional neural networks has significant implications for automated underwater fishing operations. Among these, object detection algorithms based on underwater robots have become a hot topic in both academic and applied rese...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jie Chen, Xiaochun Hu, Jiahao Lu, Yan Chen and Xin Huang
The number of wheat ears per unit area is crucial for assessing wheat yield, but automated wheat ear counting still faces significant challenges due to factors like lighting, orientation, and density variations. Departing from most static image analysis ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lei Shi, Jiayue Sun, Yuanbo Dang, Shaoqi Zhang, Xiaoyun Sun, Lei Xi and Jian Wang
Utilizing image data for yield estimation is a key topic in modern agriculture. This paper addresses the difficulty of counting wheat spikelets using images, to improve yield estimation in wheat fields. A wheat spikelet image dataset was constructed with...
ver más
|
|
|
|
|
|
|
|
|
|
|
Rio Arifando, Shinji Eto and Chikamune Wada
Object detection is crucial for individuals with visual impairment, especially when waiting for a bus. In this study, we propose a lightweight and highly accurate bus detection model based on an improved version of the YOLOv5 model. We propose integratin...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chuanyun Wang, Linlin Meng, Qian Gao, Jingjing Wang, Tian Wang, Xiaona Liu, Furui Du, Linlin Wang and Ershen Wang
Aiming at the problems of low detection accuracy and large computing resource consumption of existing Unmanned Aerial Vehicle (UAV) detection algorithms for anti-UAV, this paper proposes a lightweight UAV swarm detection method based on You Only Look Onc...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ziyi Li, Yang Li, Yanping Wang, Guangda Xie, Hongquan Qu and Zhuoyang Lyu
With the rapid development of deep learning, more and more complex models are applied to 3D point cloud object detection to improve accuracy. In general, the more complex the model, the better the performance and the greater the computational resource co...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiehui Liu, Hongchao Qiao, Lijie Yang and Jinxi Guo
During the operation of the belt conveyor, foreign objects such as large gangue and anchor rods may be mixed into the conveyor belt, resulting in tears and fractures, which affect transportation efficiency and production safety. In this paper, we propose...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yuhang Xie, Xiyu Zhong, Jialei Zhan, Chang Wang, Nating Liu, Lin Li, Peirui Zhao, Liujun Li and Guoxiong Zhou
|
|
|
|
|
|
|
|
|
|
|
Priyank Kalgaonkar and Mohamed El-Sharkawy
Object detection, a more advanced application of computer vision than image classification, utilizes deep neural networks to predict objects in an input image and determine their locations through bounding boxes. The field of artificial intelligence has ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Liming Zhou, Xiaohan Rao, Yahui Li, Xianyu Zuo, Baojun Qiao and Yinghao Lin
In recent years, significant progress has been obtained in object detection using Convolutional Neural Networks (CNNs). However, owing to the particularity of Remote Sensing Images (RSIs), common object detection methods are not well suited for RSIs. Aim...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhangqi Yang, Ye Li, Bo Wang, Shuoshuo Ding and Peng Jiang
For unmanned surface vehicles (USVs), perception and control are commonly performed in embedded devices with limited computing power. Sea surface object detection can provide sufficient information for USVs, while most algorithms have poor real-time perf...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yutan Wang, Zhenwei Xing, Liefei Ma, Aili Qu and Junrui Xue
The detection of Lingwu long jujubes in a natural environment is of great significance for robotic picking. Therefore, a lightweight network of target detection based on the SSD (single shot multi-box detector) is presented to meet the requirements of a ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jun Wang, Shuman Qi, Chao Wang, Jin Luo, Xin Wen and Rui Cao
With the increasing maturity of underwater agents-related technologies, underwater object recognition algorithms based on underwater robots have become a current hotspot for academic and applied research. However, the existing underwater imaging conditio...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wendou Yan, Xiuying Wang and Shoubiao Tan
This paper proposes the You Only Look Once (YOLO) dependency fusing attention network (DFAN) detection algorithm, improved based on the lightweight network YOLOv4-tiny. It combines the advantages of fast speed of traditional lightweight networks and high...
ver más
|
|
|
|
|
|