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Chunling Wang, Tianyi Hang, Changke Zhu and Qi Zhang
The Czech Republic is one of the countries along the Belt and Road Initiative, and classifying land cover in the Czech Republic helps to understand the distribution of its forest resources, laying the foundation for forestry cooperation between China and...
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Qianjing Li, Jia Tian and Qingjiu Tian
The combination of multi-temporal images and deep learning is an efficient way to obtain accurate crop distributions and so has drawn increasing attention. However, few studies have compared deep learning models with different architectures, so it remain...
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Muhammad Akhtar, Iqbal Murtza, Muhammad Adnan and Ayesha Saadia
Natural scene classification, which has potential applications in precision agriculture, environmental monitoring, and disaster management, poses significant challenges due to variations in the spatial resolution, spectral resolution, texture, and size o...
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Jun Wu, Xinyi Sun, Lei Qu, Xilan Tian and Guangyu Yang
Recently, deep learning tools have made significant progress in hyperspectral image (HSI) classification. Most of existing methods implement a patch-based classification manner which may cause training test information leakage or waste labeled informatio...
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Nan Jia, Bin Li, Jun Zhu, Haifeng Wang, Yuliang Zhao and Wenwen Zhao
The identification of chicken sex before hatching is an important problem in large-scale breeding applications in the poultry industry. This paper systematically reviews the key techniques for in ovo sexing of chicken eggs before hatching and presents re...
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Sriniketan Sridhar, Anibal Romney and Vidya Manian
Mild Cognitive Impairment (MCI) and Alzheimer?s Disease (AD) are frequently associated with working memory (WM) dysfunction, which is also observed in various neural psychiatric disorders, including depression, schizophrenia, and ADHD. Early detection of...
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Wuttichai Boonpook, Yumin Tan, Attawut Nardkulpat, Kritanai Torsri, Peerapong Torteeka, Patcharin Kamsing, Utane Sawangwit, Jose Pena and Montri Jainaen
Using deep learning semantic segmentation for land use extraction is the most challenging problem in medium spatial resolution imagery. This is because of the deep convolution layer and multiple levels of deep steps of the baseline network, which can cau...
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Na Luo, Yunlong Li, Baohua Yang, Biyun Liu and Qianying Dai
The content of tea polyphenols (TP) is one of the important indicators for judging the quality of tea. Accurate and non-destructive estimation technology for tea polyphenol content has attracted more and more attention, which has become a key technology ...
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Jihyoung Ryu and Yeongmin Jang
Convolution neural networks have received much interest recently in the categorization of hyperspectral images (HSI). Deep learning requires a large number of labeled samples in order to optimize numerous parameters due to the expansion of architecture d...
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Ali Salimian, Evan Haine, Cova Pardo-Sanchez, Abul Hasnath and Hari Upadhyaya
The spectral emission data from the plasma glow of various sputtering targets containing indium oxide, zinc oxide, and tin oxide were obtained. The plasma was generated at various power and chamber pressures. These spectral data were then converted into ...
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