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Titlebook: Networking, Intelligent Systems and Security; Proceedings of NISS Mohamed Ben Ahmed,Horia-Nicolai L. Teodorescu,Anou Conference proceeding

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Detection of Human Activities in Wildlands to Prevent the Occurrence of Wildfires Using Deep Learnining images to detect human activity in wildlands to prevent fire occurrence that can be caused by humans. Human activities can be presented as any human interaction with wildlands, and it can be roads, cars, vehicles, homes, human shapes, agricultural lands, golfs, airplanes, or any other human proo
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Tomato Plant Disease Detection and Classification Using Convolutional Neural Network Architectures Ttheir people. But unfortunately, several states are suffering enormously and are unable to join the standing up to satisfy their populations in sufficient quantities. Despite technological advances in scientific research and advances in genetics to improve the quality and quantity of agricultural pr
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Skin Detection Based on Convolutional Neural Networkting regions containing the skin in a digital image. This problem has become the subject of considerable research in the scientific community where a variety of approaches has been proposed in the literature; however, few recent reviews exist. Our principal goal in this paper is to extract skin regi
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CRAN: An Hybrid CNN-RNN Attention-Based Model for Arabic Machine Translationed approaches and Recurrent Neural Network (RNN)-based techniques have shown different capabilities in representing a piece of text. In this work, an hybrid CNN-RNN attention-based neural network is proposed. During training, Adam optimizer algorithm is used, and then, a popular regularization techn
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Impact of the CNN Patch Size in the Writer Identification right writer of a handwritten text. The introduction of deep learning has made it possible to achieve unprecedented records in the field. However, the question to ask, what size of patch to use to train a CNN model in order to have the best performance? In our paper, we try to find an answer to thi
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