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Corn Yield Prediction Model with Deep Neural Networks for Smallholder Farmer Decision Support System
Given the nonlinearity of the interaction between weather and soil variables, a deep neural network regressor (DNNR) is carefully designed with consideration to the depth, number of neurons of the hidden layers, and the hyperparameters with their optimizations.
Understanding Unconventional Preprocessors in Deep Convolutional Neural Networks for Face Identification
Others are termed the unconventional preprocessors, they are: color space converters; HSV, CIE L*a*b* and YCBCR, grey-level resolution preprocessors; full-based and plane-based image quantization, illumination normalization and insensitive feature preprocessing using: histogram equalization (HE), local contrast normalization (LN) and complete face structural pattern (CFSP).
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