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Titlebook: Artificial Intelligence and Its Applications; Proceeding of the 2n Brahim Lejdel,Eliseo Clementini,Louai Alarabi Conference proceedings 202

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Residual Neural Network for Predicting Super-Enhancers on Genome Scale, computer vision problems. It uses skip connections over some layer blocks to avoid vanishing gradient problem. Currently, many researches are focused to test and prove the efficiency of the ResNet on different domains such as genomics..In this paper, we propose a new ResNet model for predicting sup
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Machine Learning Algorithms for Big Data Mining Processing: A Review,uires automation, which leads to serious consideration of the use of machine learning algorithms. Machine learning helps us make decisions if there is no right way to solve a problem identified in previous knowledge bases, and that is, too, one of the most widely used analysis and modeling tools for
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,Deep Neural Network Based TensorFlow Model for IoT Lightweight Cipher Attack,rent limitations in size, storage memory, and power consumption limit its specific functionality in the secure transmission of sensitive information, where the development of lightweight ciphers responds adequately to these limitations. However, the conventional cryptanalysis of these modern ciphers
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,Sentiment Analysis of Algerian Dialect Using a Deep Learning Approach,ment offers us a great interest for research, marketing and industry. With millions of comments and tweeting published every day, the information available on the Internet and in social media has become a gold mine for companies developing in their production, management and distribution. In this ar
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,Do We Need Change Detection for Dynamic Optimization Problems?: A Survey,t be powerful enough to track new optima. For population based algorithms this is referred to as diversity loss problem. Furthermore, the memory of old optima becomes outdated and if not correctly dealt with, the evolution of the search process may be misguided. Recently, a new interesting trend in
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