Deep Learning, A Key Technology Enabler for Computer Vision Systems: A Tractica Report

FREMONT, CA: Tractica, a market research company, states in a new whitepaper that Deep Learning is an important enabling technology that is most applicable to computer vision systems. The whitepaper titled “Deep Learning Use Cases for Computer Vision” includes Deep Learning as an alternative to traditional programming approaches as it is cost effective, more accurate, and more reliable.

Since Deep Learning is data agnostic, it is also suitable to be used in almost every enterprise vertical market. The whitepaper examines Deep Learning use cases; as to how it is being used in various industry verticals such as Digital Media, Healthcare, Agriculture, Retail, Manufacturing, and Other Industries.

Deep learning use cases featured in the white paper include static image recognition, classification, and tagging, digital radiology analysis, agricultural crop health analysis, clinical trial medication compliance, clothes and accessories sizing and fitting, and industrial automation quality assurance.

"Deep learning" is the new trend in Machine Learning. It promises general, powerful, and fast machine learning, moving the world closer to Artificial Intelligence. An algorithm is deep if the input is passed through several non-linearities before being output. Most modern learning algorithms are "shallow". Deep learning is motivated by intuition, theoretical arguments from circuit theory, empirical results, and current knowledge of neuroscience.

“Some of the most successful companies in the world have been early adopters of deep learning for computer vision applications,” says principal analyst Bruce Daley. “Although the enterprise market for deep learning is still small in relation to the total enterprise software sector, the variety, breadth, and scope of the applications that deep learning is being considered for suggests that a tremendous growth opportunity exists.”

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