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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...
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Han Li, Yiqun Dong, Yunxiao Liu and Jianliang Ai
In recent years, unmanned aerial vehicles (UAV) have been increasingly used in power line inspections. Birds often nest on transmission line towers, which threatens safe power line operation. The existing research on bird?s nest inspection using UAVs mai...
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Qing Dong, Lina Sun, Tianxin Han, Minqi Cai and Ce Gao
Timely and effective pest detection is essential for agricultural production, facing challenges such as complex backgrounds and a vast number of parameters. Seeking solutions has become a pressing matter. This paper, based on the YOLOv5 algorithm, develo...
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Eduardo Assunção, Pedro D. Gaspar, Khadijeh Alibabaei, Maria P. Simões, Hugo Proença, Vasco N. G. J. Soares and João M. L. P. Caldeira
Within the scope of precision agriculture, many applications have been developed to support decision making and yield enhancement. Fruit detection has attracted considerable attention from researchers, and it can be used offline. In contrast, some applic...
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Zonglei Lyu and Jia Luo
Airport apron carries a lot of preparations for flight operation, and the advancement of its various tasks is of great significance to the flight operation. In order to build a more intelligent and easy-to-deploy airport apron operation analysis guarante...
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Peihao Huang, Tao Wang, Lin Ding, Huhuang Yu, Yong Tang and Dianle Zhou
The real-time fault detection and diagnosis algorithm of a liquid rocket engine is the basis of online reconfiguration of guidance and the control system of a launch vehicle, which is directly related to the success or failure of space mission. Based on ...
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Junsheng Liu, Guangze Zhao, Shuangxi Liu, Yi Liu, Huawei Yang, Jingwei Sun, Yinfa Yan, Guoqiang Fan, Jinxing Wang and Hongjian Zhang
In the realm of automated apple picking operations, the real-time monitoring of apple maturity and diameter characteristics is of paramount importance. Given the constraints associated with feature detection of apples in automated harvesting, this study ...
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Peng Li, Yibing Fan, Zhengyang Cai, Zhiyu Lyu and Weijie Ren
Marine biological object detection is of great significance for the exploration and protection of underwater resources. There have been some achievements in visual inspection for specific objects based on machine learning. However, owing to the complex i...
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Yawar Rehman, Hafsa Amanullah, Dost Muhammad Saqib Bhatti, Waqas Tariq Toor, Muhammad Ahmad and Manuel Mazzara
Traffic sign recognition is a key module of autonomous cars and driver assistance systems. Traffic sign detection accuracy and inference time are the two most important parameters. Current methods for traffic sign recognition are very accurate; however, ...
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Dana Utebayeva, Lyazzat Ilipbayeva and Eric T. Matson
The detection and classification of engine-based moving objects in restricted scenes from acoustic signals allow better Unmanned Aerial System (UAS)-specific intelligent systems and audio-based surveillance systems. Recurrent Neural Networks (RNNs) provi...
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Francisco Melo Pereira and Rute C. Sofia
This paper provides an analysis of two machine learning algorithms, density-based spatial clustering of applications with noise (DBSCAN) and the local outlier factor (LOF), applied in the detection of outliers in the context of a continuous framework for...
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Lwando Nkuzo, Malusi Sibiya and Elisha Didam Markus
Using a safety belt is crucial for preventing severe injuries and fatalities during vehicle accidents. In this paper, we propose a real-time vehicle occupant safety belt detection system based on the YOLOv7 (You Only Look Once version seven) object detec...
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Vijayakumar Varadarajan, Dweepna Garg and Ketan Kotecha
Deep learning is a relatively new branch of machine learning in which computers are taught to recognize patterns in massive volumes of data. It primarily describes learning at various levels of representation, which aids in understanding data that includ...
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Xueliang Zhu, Dasen Wang, Fengming Nie, Bingcai Liu, Hongjun Wang and Ailing Tian
This paper proposes a real-time compensated pentaprism scanning wavefront detection method to achieve real-time compensation for scanning errors occurring during prism movement along a guide rail. The method is based on existing pentaprism scanning wavef...
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Kyungmin Jo, Yuna Choi, Jaesoon Choi and Jong Woo Chung
More than half of post-operative complications can be prevented, and operation performances can be improved based on the feedback gathered from operations or notifications of the risks during operations in real time. However, existing surgical analysis m...
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Jiansen Zhao, Fengchuan Song, Guobao Gong and Shengzheng Wang
Accurate and real-time monitoring of the shoreline through cameras is an invaluable guarantee for the safety of near-shore navigation and berthing of unmanned surface vehicles; existing shoreline detection methods cannot meet both these requirements. The...
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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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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...
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Omar Capetillo-Contreras, Francisco David Pérez-Reynoso, Marco Antonio Zamora-Antuñano, José Manuel Álvarez-Alvarado and Juvenal Rodríguez-Reséndiz
The world population is expected to grow to around 9 billion by 2050. The growing need for foods with high protein levels makes aquaculture one of the fastest-growing food industries in the world. Some challenges of fishing production are related to obso...
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Hailiang Gong, Xi Wang and Weidong Zhuang
This study focuses on real-time detection of maize crop rows using deep learning technology to meet the needs of autonomous navigation for weed removal during the maize seedling stage. Crop row recognition is affected by natural factors such as soil expo...
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