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Se-Yeong Oh, Junho Jeong, Sang-Woo Kim, Young-Uk Seo and Joosang Youn
Along with the recent development of artificial intelligence technology, convergence services that apply technology are undergoing active development in various industrial fields. In particular, artificial intelligence-based object recognition technologi...
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Yanxin Hu, Gang Liu, Zhiyu Chen and Jianwei Guo
In practical applications, the intelligence of wheeled mobile robots is the trend of future development. Object detection for wheeled mobile robots requires not only the recognition of complex surroundings, but also the deployment of algorithms on resour...
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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...
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Wei Ji, Yu Pan, Bo Xu and Juncheng Wang
In order to enable the picking robot to detect and locate apples quickly and accurately in the orchard natural environment, we propose an apple object detection method based on Shufflenetv2-YOLOX. This method takes YOLOX-Tiny as the baseline and uses the...
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Liang Huang, Mulan Qiu, Anze Xu, Yu Sun and Juanjuan Zhu
Road traffic elements comprise an important part of roads and represent the main content involved in the construction of a basic traffic geographic information database, which is particularly important for the development of basic traffic geographic info...
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Joanna Kulawik, Mariusz Kubanek and Sebastian Garus
This research aimed to develop a system for classifying horizontal road signs as correct or with poor visibility. In Poland, road markings are applied by using a specialized white, reflective paint and require periodic repainting. Our developed system is...
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Yuanzhou Zheng, Peng Liu, Long Qian, Shiquan Qin, Xinyu Liu, Yong Ma and Ganjun Cheng
To improve the navigation safety of inland river ships and enrich the methods of environmental perception, this paper studies the recognition and depth estimation of inland river ships based on binocular stereo vision (BSV). In the stage of ship recognit...
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Yanjun Li, Takaaki Yoshimura, Yuto Horima and Hiroyuki Sugimori
The detection of coronary artery stenosis is one of the most important indicators for the diagnosis of coronary artery disease. However, stenosis in branch vessels is often difficult to detect using computer-aided systems and even radiologists because of...
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Hamed Raoofi, Asa Sabahnia, Daniel Barbeau and Ali Motamedi
Traditional methods of supervision in the construction industry are time-consuming and costly, requiring significant investments in skilled labor. However, with advancements in artificial intelligence, computer vision, and deep learning, these methods ca...
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Xin Li, Cheng Wang, Haijuan Ju and Zhuoyue Li
Aiming at the problems of low efficiency and poor accuracy in conventional surface defect detection methods for aero-engine components, a surface defect detection model based on an improved YOLOv5 object detection algorithm is proposed in this paper. Fir...
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Wangyuan Zhao, Fenglei Han, Zhihao Su, Xinjie Qiu, Jiawei Zhang and Yiming Zhao
It is promising to detect or maintain subsea X-trees using a remote operated vehicle (ROV). In this article, an efficient recognition model for the subsea X-tree component is proposed to assist in the autonomous operation of unmanned underwater maintenan...
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Jiapeng Cui and Feng Tan
Rice diseases are extremely harmful to rice growth, and achieving the identification and rapid classification of rice disease spots is an essential means to promote intelligent rice production. However, due to the large variety of rice diseases and the s...
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Xiaobin Hong, Bin Cui, Weiguo Chen, Yinhui Rao and Yuanming Chen
Aiming at the problem that multi-ship target detection and tracking based on cameras is difficult to meet the accuracy and speed requirements at the same time in some complex scenes, an improved YOLOv4 algorithm is proposed, which simplified the network ...
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Shilin Li, Shujuan Zhang, Jianxin Xue, Haixia Sun and Rui Ren
The efficient identification of the field flat jujube is the first condition to realize its automated picking. Consequently, a lightweight algorithm of target identification based on improved YOLOv5 (you only look once) is proposed to meet the requiremen...
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Shuzhi Su, Runbin Chen, Xianjin Fang, Yanmin Zhu, Tian Zhang and Zengbao Xu
This study proposes a novel lightweight grape detection method. First, the backbone network of our method is Uniformer, which captures long-range dependencies and further improves the feature extraction capability. Then, a Bi-directional Path Aggregation...
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Xingdong Sun, Yukai Zheng, Delin Wu and Yuhang Sui
The key technology of automated apple harvesting is detecting apples quickly and accurately. The traditional detection methods of apple detection are often slow and inaccurate in unstructured orchards. Therefore, this article proposes an improved YOLOv5s...
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Bo Xu, Xiang Cui, Wei Ji, Hao Yuan and Juncheng Wang
Apple grading is an essential part of the apple marketing process to achieve high profits. In this paper, an improved YOLOv5 apple grading method is proposed to address the problems of low grading accuracy and slow grading speed in the apple grading proc...
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Wang Yang, Junhui Xi, Zhihao Wang, Zhiheng Lu, Xian Zheng, Debang Zhang and Yu Huang
Cassava (Manihot esculenta Crantz) is a major tuber crop worldwide, but its mechanized harvesting is inefficient. The digging?pulling cassava harvester is the primary development direction of the cassava harvester. However, the harvester clamping?pulling...
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Xinle Zhang, Jian Cui, Huanjun Liu, Yongqi Han, Hongfu Ai, Chang Dong, Jiaru Zhang and Yunxiang Chu
Soybean in the field has a wide range of intermixed weed species and a complex distribution status, and the weed identification rate of traditional methods is low. Therefore, a weed identification method is proposed based on the optimized Faster R-CNN al...
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Alexey N. Beskopylny, Evgenii M. Shcherban?, Sergey A. Stel?makh, Levon R. Mailyan, Besarion Meskhi, Irina Razveeva, Alexey Kozhakin, Diana El?shaeva, Nikita Beskopylny and Gleb Onore
The creation and training of artificial neural networks with a given accuracy makes it possible to identify patterns and hidden relationships between physical and technological parameters in the production of unique building materials, predict mechanical...
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