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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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Nils Hütten, Miguel Alves Gomes, Florian Hölken, Karlo Andricevic, Richard Meyes and Tobias Meisen
Quality assessment in industrial applications is often carried out through visual inspection, usually performed or supported by human domain experts. However, the manual visual inspection of processes and products is error-prone and expensive. It is ther...
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Joaquim Miguel, Pedro Mendonça, Agnelo Quelhas, João M. L. P. Caldeira and Vasco N. G. J. Soares
Hiking and cycling have become popular activities for promoting well-being and physical activity. Portugal has been investing in hiking and cycling trail infrastructures to boost sustainable tourism. However, the lack of reliable data on the use of these...
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Arturs Kempelis, Inese Polaka, Andrejs Romanovs and Antons Patlins
Urban agriculture presents unique challenges, particularly in the context of microclimate monitoring, which is increasingly important in food production. This paper explores the application of convolutional neural networks (CNNs) to forecast key sensor m...
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Beata Baziak, Marek Bodziony and Robert Szczepanek
Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks for which automation was analyzed consisted of estimat...
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Weihong Ma, Xiangyu Qi, Yi Sun, Ronghua Gao, Luyu Ding, Rong Wang, Cheng Peng, Jun Zhang, Jianwei Wu, Zhankang Xu, Mingyu Li, Hongyan Zhao, Shudong Huang and Qifeng Li
Acquiring phenotypic data from livestock constitutes a crucial yet cumbersome phase in the breeding process. Traditionally, obtaining livestock phenotypic data primarily involves manual, on-body measurement methods. This approach not only requires extens...
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Juanli Jing, Menglin Zhai, Shiqing Dou, Lin Wang, Binghai Lou, Jichi Yan and Shixin Yuan
The accurate identification of citrus fruits is important for fruit yield estimation in complex citrus orchards. In this study, the YOLOv7-tiny-BVP network is constructed based on the YOLOv7-tiny network, with citrus fruits as the research object. This n...
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Oscar Leonardo García-Navarrete, Oscar Santamaria, Pablo Martín-Ramos, Miguel Ángel Valenzuela-Mahecha and Luis Manuel Navas-Gracia
Corn (Zea mays L.) is one of the most important cereals worldwide. To maintain crop productivity, it is important to eliminate weeds that compete for nutrients and other resources. The eradication of these causes environmental problems through the use of...
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Zimei Zhang, Jianwei Xiao, Wenjie Wang, Magdalena Zielinska, Shanyu Wang, Ziliang Liu and Zhian Zheng
Angelica sinensis (Oliv.) Diels, a member of the Umbelliferae family, is commonly known as Danggui (Angelica sinensis, AS). AS has the functions of blood tonic, menstrual pain relief, and laxatives. Accurate classification of AS grades is crucial for eff...
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Zhengyang Zhong, Lijun Yun, Feiyan Cheng, Zaiqing Chen and Chunjie Zhang
This paper proposes a lightweight and efficient mango detection model named Light-YOLO based on the Darknet53 structure, aiming to rapidly and accurately detect mango fruits in natural environments, effectively mitigating instances of false or missed det...
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