Titlebook: Advances in Data and Information Sciences; Proceedings of ICDIS Shailesh Tiwari,Munesh C. Trivedi,Brajesh Kumar Si Conference proceedings 2

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Cause related Marketing in Deutschlandgeneralization in deep neural networks. A survey of studies is conducted that aim to better understand the theoretical bounds of neural networks (NN). An empathetic knowledge of the generalization theory will enable researchers/developers to model more cost-effective and powerful networks.

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M. Victoria Carrillo-Duran,Ana Castillo-Diazes. Notably, convolutional neural networks and recurrent neural networks are significantly employed for text recognition and word spotting. In this article, the most important techniques of deep learning used in the recognition Arabic-adapted scripts such as Urdu, Arabic, and Pashto have been summarized and compared.

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Evaluation Methods of Cause-Effect Pairsformed feature selection and considered only those features that have strong correlation with target feature, i.e., effort. The mean magnitude relative error (MMRE) and PRED(25) results demonstrate that utilizing elastic net as the base learner for AdaBoost outperforms the other models.

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On Being Ontologically Unseriousmputation schemes to yield best in class recommendation maintaining a high diversity index. Experimentations have indicated that the proposed BiCropRec framework has yielded much higher performance measures when compared to the baseline models. BiCropRec has furnished an overall F-measure of 97.66% with a very low false discovery rate of 0.03.

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Semantic Properties of c-e Structures, foreground and background differences. However, detective efficiency is relatively poor in the case of images that can’t differentiate between foreground and background. In most instances of compositional range, heat treatment, and magnification, the proposed image processing technique shows promising results in UHCS SEM images.