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Conditional Generative Adversarial Networks (GANs) for cross-domain image-to-image translation have made much progress recently [7, 8, 21, 12, 4, 18]. Depending on the task complexity, thousands to millions of labeled image pairs are needed to train a conditional GAN. However, human labeling is expensive, even impractical, and large quantities of data may not always be available. Inspired by dual...
A new algorithm for learning binary codes is presented using randomized initial assignments of bit labels to classes followed by iterative refinement to minimize intraclass Hamming distance. This Randomized Intraclass-Distance Minimizing Binary Codes (RIDMBC) algorithm is introduced in the context of face recognition, an area of biometrics where binary codes have rarely been used (unlike iris recognition)...
How to effectively monitor water quality of Coastal and inland waters by optical remote sensing has always been a difficulty. This study develops a neural network model to improve the accuracy in monitoring water quality of Lake Taihu, China, a large shallow subtropical lake. A three-layer back-propagation neural network is built up to estimate concentrations of chlorophyll-a, total suspended matter...
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