21   Artículos

 
en línea
Yu Zhang, Jiajun Niu, Zezhong Huang, Chunlei Pan, Yueju Xue and Fengxiao Tan    
An algorithm model based on computer vision is one of the critical technologies that are imperative for agriculture and forestry planting. In this paper, a vision algorithm model based on StyleGAN and improved YOLOv5s is proposed to detect sandalwood tre... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
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... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Ying-Tung Hsiao, Jia-Shing Sheu, Hsu Ma     Pág. 42 - 49
Revista: Advances in Technology Innovation    Formato: Electrónico

 
en línea
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... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Ka Seng Chou, Teng Lai Wong, Kei Long Wong, Lu Shen, Davide Aguiari, Rita Tse, Su-Kit Tang and Giovanni Pau    
This research addresses the challenges of visually impaired individuals? independent travel by avoiding obstacles. The study proposes a distance estimation method for uncontrolled three-dimensional environments to aid navigation towards labeled target ob... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Rui Ren, Haixia Sun, Shujuan Zhang, Ning Wang, Xinyuan Lu, Jianping Jing, Mingming Xin and Tianyu Cui    
To detect quickly and accurately ?Yuluxiang? pear fruits in non-structural environments, a lightweight YOLO-GEW detection model is proposed to address issues such as similar fruit color to leaves, fruit bagging, and complex environments. This model impro... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Viet Q. Vu, Minh-Quang Tran, Mohammed Amer, Mahesh Khatiwada, Sherif S. M. Ghoneim and Mahmoud Elsisi    
Facial mask detection technology has become increasingly important even beyond the context of the COVID-19 pandemic. Along with the advancement in facial recognition technology, face mask detection has become a crucial feature for various applications. T... ver más
Revista: Information    Formato: Electrónico

 
en línea
Huishan Li, Lei Shi, Siwen Fang and Fei Yin    
Aiming at the problem of accurately locating and identifying multi-scale and differently shaped apple leaf diseases from a complex background in natural scenes, this study proposed an apple leaf disease detection method based on an improved YOLOv5s model... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Pavel Laptev, Sergey Litovkin, Sergey Davydenko, Anton Konev, Evgeny Kostyuchenko and Alexander Shelupanov    
This paper compares neural networks, specifically Unet, MobileNetV2, VGG16 and YOLOv4-tiny, for image segmentation as part of a study aimed at finding an optimal solution for price tag data analysis. The neural networks considered were trained on an indi... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
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
Revista: Future Internet    Formato: Electrónico

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