Pattern Inversion as a Pattern Recognition Method for Machine Learning
نویسندگان
چکیده
Abstract Artificial neural networks use a lot of coefficients that take great deal computing power for their adjustment, especially if deep learning are employed. However, there exist coefficients-free extremely fast indexing-based technologies work, instance, in Google search engines, genome sequencing, etc. The paper discusses the methods pattern recognition. It is shown recognition applications such indexing replace with inverse patterns fully inverted files, which typically employed engines. Not only inversion provides automatic feature extraction, distinguishing mark learning, but, unlike supports almost instantaneous consequence absence coefficients. formalism makes on novel transform and its application unsupervised instant learning. Examples demonstrate view-angle independent three-dimensional objects, as cars, against arbitrary background, prediction remaining useful life aircraft other applications. In conclusion, it noted that, neurophysiology, function neocortical mini-column has been widely debated since 1957. This hypothesizes mathematically, cortical can be described an pattern, physically serves connection multiplier expanding associations inputs relevant classes.
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ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2022
ISSN: ['1742-6588', '1742-6596']
DOI: https://doi.org/10.1088/1742-6596/2224/1/012002