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Global digitalization is associated with the widespread introduction of artificial intelligence technologies based on artificial neural networks. Such networks reflect the behavior of the human brain, allowing computer programs to recognize patterns and solve various problems from image recognition to the search for diseases.
Neural networks are based on specially configured learning algorithms for specific tasks that allow classifying and clustering disparate data at a high speed, which allows neural networks to recognize speech, text or images in minutes. However, despite the already known advantages of neural networks, various studies are currently continuing, aimed both at optimizing the learning processes of neural networks, and at choosing the best neural network structure in accordance with the features and complexities of the problem proposed for a system equipped with artificial intelligence.
One of these research areas is the development of convolutional neural networks used for the purposes of computer vision technologies. The above-mentioned networks are able to create music and paintings, detect diseases and solve many other tasks that were previously considered exclusively anthropic — solvable only by humans. However, despite all the advantages of such networks, their possibilities are not unlimited, in addition, convolutional neural networks are quite vulnerable to various kinds of attacks, so research in the field of convolutional networks continues, and the topic of the development of such networks is one of the most relevant in the field of neural network technologies.
Keywords:neural networks, global digitalization, neural network technologies, convolutional neural networks, vulnerability of neural networks
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