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Agricola

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Agricola

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Agricola

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A novel method combining deep learning with the Kennard–Stone algorithm for training dataset selection for image‐based rice seed variety identification.

• Authors : Jin, Chen; Zhou, Xinyue; He, Mengyu

Subjects: MACHINE learning; HYBRID rice; DEEP learning

• Source: Journal of the Science of Food & Agriculture; Oct2024, Vol. 104 Issue 13, p8332-8342, 11p

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Banana Bunch Weight Estimation and Stalk Central Point Localization in Banana Orchards Based on RGB-D Images.

• Authors : Zhou, Lei; Yang, Zhou; Deng, Fuqin

Subjects: BANANAS; ORCHARD management; ORCHARDS

• Source: Agronomy; Jun2024, Vol. 14 Issue 6, p1123, 16p

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OSS reliability assessment method based on deep learning and independent Wiener data preprocessing.

• Authors : Tamura, Yoshinobu; Miyamoto, Shoichiro; Zhou, Lei

• Source: International Journal of Systems Assurance Engineering & Management; Jun2024, Vol. 15 Issue 6, p2668-2676, 9p

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Agricola

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Accurate atomic scanning transmission electron microscopy analysis enabled by deep learning.

• Authors : Chu, Tianshu; Zhou, Lei; Zhang, Bowei

Subjects: SCANNING transmission electron microscopy; DEEP learning; MACHINE learning

• Source: Nano Research; Apr2024, Vol. 17 Issue 4, p2971-2980, 10p

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ADF-Net: An Attention-Guided Dual-Branch Fusion Network for Building Change Detection near the Shanghai Metro Line Using Sequences of TerraSAR-X Images.

• Authors : Chen, Peng; Lin, Jinxin; Zhao, Qing

Subjects: DEEP learning; MACHINE learning; SPECKLE interferenceSHANGHAI (China)

• Source: Remote Sensing; Mar2024, Vol. 16 Issue 6, p1070, 21p

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Arbitrary Multifunctional Vortex Beam Designed by Deep Neural Network.

• Authors : Peng, Pu; Liu, Zhengchang; Dai, Changhong

Subjects: ARTIFICIAL neural networks; VECTOR beams; OPTICAL communications

• Source: Advanced Optical Materials; Feb2024, Vol. 12 Issue 6, p1-7, 7p

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