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Vision inference is the process of the eye, recognizing an object, analyzing the same and reconstructing a complete picture of an object. Unlike some mental processes like computing an addition, or reasoning for a decision in a chess game, vision inference is a mental ability that the person involved is not consciously aware of. As a result, many people including experienced researchers often underestimate the difficulty of recognizing the image while modeling the same. The earliest pattern recognition research dates back to 1966 when Marvin Minsky and Seymour Papert tried developing an object recognition system (Papert 1966). Yet it has taken more than 50 years to develop a system for image classification which is similar in accuracy to an average person. In the last decade, machine learning has succeeded in tasks like identifying a wide variety of objects and faces in realistic situations and contexts.
| Autorius: | Joshua Arul Kumar R |
| Leidėjas: | Hussaini Begum |
| Išleidimo metai: | 2024 |
| Knygos puslapių skaičius: | 144 |
| ISBN-13: | 9798227987655 |
| Formatas: | 280 x 216 x 9 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „TACKLING THE IMAGE CLASSIFICATION PROBLEM WITH SPIKING NEURAL NETWORK TECHNIQUE“
