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Jingming Wu, Tiecheng Bai and Xu Li
Chlorophyll content is highly susceptible to environmental changes, and monitoring these changes can be a crucial tool for optimizing crop management and providing a foundation for research in plant physiology and ecology. This is expected to deepen our ...
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Mingyoung Jeng, Alvir Nobel, Vinayak Jha, David Levy, Dylan Kneidel, Manu Chaudhary, Ishraq Islam, Evan Baumgartner, Eade Vanderhoof, Audrey Facer, Manish Singh, Abina Arshad and Esam El-Araby
Convolutional neural networks (CNNs) have proven to be a very efficient class of machine learning (ML) architectures for handling multidimensional data by maintaining data locality, especially in the field of computer vision. Data pooling, a major compon...
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Alfadhl Y. Khaled, Nader Ekramirad, Kevin D. Donohue, Raul T. Villanueva and Akinbode A. Adedeji
The demand for high-quality apples remains strong throughout the year, as they are one of the top three most popular fruits globally. However, the apple industry faces challenges in monitoring and managing postharvest losses due to invasive pests during ...
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Nader Ekramirad, Alfadhl Y. Khaled, Kevin D. Donohue, Raul T. Villanueva and Akinbode A. Adedeji
Codling moth (CM) is a major apple pest. Current manual method of detection is not very effective. The development of nondestructive monitoring and detection methods has the potential to reduce postharvest losses from CM infestation. Previous work from o...
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Qingqing Hong, Xinyi Zhong, Weitong Chen, Zhenghua Zhang and Bin Li
Hyperspectral images (HSIs) are pivotal in various fields due to their rich spectral?spatial information. While convolutional neural networks (CNNs) have notably enhanced HSI classification, they often generate redundant spatial features. To address this...
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Bin Wang, Hua Yang, Shujuan Zhang and Lili Li
Detection of skin defects in Cerasus humilis fruit is a critical process to guarantee its quality and price. This study presents a valid method for the detection of defective features in Cerasus humilis fruits based on hyperspectral imaging. A total of 4...
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Chaitali Bhattacharyya and Sungho Kim
With the development of new technologies inside car mechanisms with various sensors connected to the IoT, a new generation of automation is attracting attention. However, there are still some factors that are difficult to detect. Among them, one of the h...
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Liang Zhong, Xueyuan Chu, Jiawei Qian, Jianlong Li and Zhengguo Sun
With the rapid development of China?s industrialization and urbanization, the problem of heavy metal pollution in soil has become increasingly prominent, seriously threatening the safety of the ecosystem and human health. The development of hyperspectral...
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Lai Zhi Yong, Siti Khairunniza-Bejo, Mahirah Jahari and Farrah Melissa Muharam
Basal Stem Rot (BSR), a disease caused by Ganoderma boninense (G. boninense), has posed a significant concern for the oil palm industry, particularly in Southeast Asia, as it has the potential to cause substantial economic losses. The breeding programme ...
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Ling Wu, Yuanjuan Gong, Xiaoping Bai, Wei Wang and Zhuo Wang
The nitrogen content is an important indicator affecting corn plants? growth status. Most of the standard hyperspectral imaging-based techniques for nondestructive detection of crop nitrogen content use a single feature as the input variable of the model...
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