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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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Christine Dewi, Danny Manongga, Hendry, Evangs Mailoa and Kristoko Dwi Hartomo
Face mask detection is a technological application that employs computer vision methodologies to ascertain the presence or absence of a face mask on an individual depicted in an image or video. This technology gained significant attention and adoption du...
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Jerry Gao, Charanjit Kaur Bambrah, Nidhi Parihar, Sharvaree Kshirsagar, Sruthi Mallarapu, Hailong Yu, Jane Wu and Yunyun Yang
With the development of artificial intelligence, the intelligence of agriculture has become a trend. Intelligent monitoring of agricultural activities is an important part of it. However, due to difficulties in achieving a balance between quality and cos...
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Yujuan Cao, Jianguo Dai, Guoshun Zhang, Minghui Xia and Zhitan Jiang
This paper combines feature selection with machine learning algorithms to achieve object-oriented classification of crops in Gaofen-6 remote sensing images. The study provides technical support and methodological references for research on regional monit...
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Rui Zhang, Mingwei Yao, Zijie Qiu, Lizhuo Zhang, Wei Li and Yue Shen
Wheat breeding heavily relies on the observation of various traits during the wheat growth process. Among all traits, wheat head density stands out as a particularly crucial characteristic. Despite the realization of high-throughput phenotypic data colle...
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Huizhong Xiong, Xiaotong Gao, Ningyi Zhang, Haoxiong He, Weidong Tang, Yingqiu Yang, Yuqian Chen, Yang Jiao, Yihong Song and Shuo Yan
A novel deep learning model, DiffuCNN, is introduced in this paper, specifically designed for counting tobacco lesions in complex agricultural settings. By integrating advanced image processing techniques with deep learning methodologies, the model signi...
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Huiru Zhou, Qiang Lai, Qiong Huang, Dingzhou Cai, Dong Huang and Boming Wu
The severity of rice blast and its impacts on rice yield are closely related to the inoculum quantity of Magnaporthe oryzae, and automatic detection of the pathogen spores in microscopic images can provide a rapid and effective way to quantify pathogen i...
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Noor Ul Ain Tahir, Zuping Zhang, Muhammad Asim, Junhong Chen and Mohammed ELAffendi
Enhancing the environmental perception of autonomous vehicles (AVs) in intelligent transportation systems requires computer vision technology to be effective in detecting objects and obstacles, particularly in adverse weather conditions. Adverse weather ...
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Yuchen Dong, Heng Zhou, Chengyang Li, Junjie Xie, Yongqiang Xie and Zhongbo Li
Camouflaged object detection (COD) is an arduous challenge due to the striking resemblance of camouflaged objects to their surroundings. The abundance of similar background information can significantly impede the efficiency of camouflaged object detecti...
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Yiming Mo, Lei Wang, Wenqing Hong, Congzhen Chu, Peigen Li and Haiting Xia
The intrusion of foreign objects on airport runways during aircraft takeoff and landing poses a significant safety threat to air transportation. Small-scale Foreign Object Debris (FOD) cannot be ruled out on time by traditional manual inspection, and the...
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