Titlebook: Artificial Neural Networks in Pattern Recognition; 10th IAPR TC3 Worksh Neamat El Gayar,Edmondo Trentin,Hazem Abbas Conference proceedings

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Fetal Islet Transplantation and Pregnancy,oncerns that this increasing popularity has exacerbated issues of unfairness and discrimination toward individuals. Researchers in this field have proposed a wide variety of fairness-enhanced classifiers and fairness matrices to address these issues, but very few fairness techniques have been transl

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https://doi.org/10.1007/978-1-4615-1981-2 maximizing the minimum margin and minimizing the maximum margin. It works to improve the generalization ability of the L1 SVM (standard SVM) and LP (Linear Programming) SVM. In this paper, we discuss whether it also works for the LS (Least Squares) SVM. The minimal complexity LS SVM (MLS SVM) is tr

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Fetal Neuroimaging: Ultrasound or MRI?,ic decision-making through the ability to recognise patterns in medical images. Such technologies started showing promising results in their ability to match or outperform physicians in certain specialities and improve the quality of medical diagnosis. Convolutional neural networks are one state-of-

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,The “First Trimester (11–14 Weeks) Scan”,set is a good example of visually similar paired images to figure out how humans compare images. In this research, we consider these more generic annotated categories to build a semantic manifold distance. We introduce an atypical triplet-loss using the inverse Kullback-Leibler divergence to model t

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Fetal Morph Functional Diagnosisvariance scales. Our primary purpose is to present an approach to optimally design the WST to enhance the identification accuracy for short utterances. We describe the invariant features offered by the depth of this transform by performing simple experiments based on text-independent and text-depend

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General Remarks About Autosomal Diseases the potential of recurrent neural networks (RNNs) to handle this problem. We compare the RNN architecture to widely used convolutional neural networks (CNNs) and to some other machine learning-based and traditional non-learning algorithms on several publicly available databases. We show that the RN

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Bruce J. Kelman,Melvin R. Sikov and possibly millions of dollars of investment. It is crucial that both patent producers and consumers are able to assess the novelty of such patents and perform basic processing on them. In this work, we review approaches in the literature in patent analysis and novelty assessment that range from

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