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Historical Evolution of Deep Learning Applied to Computer Vision
Abstract
Artificial intelligence (AI) as a field of study has grown exponentially in recent years, as has applications in a multitude of fields. Within it, deep learning techniques have shown truly impressive results on all kinds of pattern recognition tasks during the last decade, and their impact will only continue to grow. To understand the virtues and weaknesses of this technology, it may be beneficial to look back at the technological advances within the field of AI and, more specifically, of computer vision and neural networks, where the ideas that gave rise to what is now known as deep learning were first developed. That is why the main objective of this chapter is to give as complete a vision as possible of the history of this technology, throughout its nearly 80 years of development. By reviewing the scientific publications that brought progress in this area of research in chronological order, this chapter will elucidate the origins of the main components of neural networks and will highlight the main contributors in this field, as well as the factors that resulted in setbacks and advances.
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