Image2Text

Image2Text technology was created by Cortica, an Israel-based startup whose technology simulates the performance of the human cortex so that computers recognize images with a high degree of accuracy.[1] Image2Text is the result of 10 years in research and development and is protected by more than 50 patents.[2]

Product Differentiation

Cortica's engine processes and recognizes images based on patterns, as the brain does, providing accuracy purporting to be comparable with that of the human brain.[1]

Previous image search solutions have relied on databases of images compiled through fingerprinting, modeling and crowdsourcing.[3] Cortica differentiates itself from these other products; patterns are clustered into digital concepts which are stored and mapped to keywords and contextual taxonomies that enable it to interpret the content appearing in the digital media.[4]

Uses

Cortica's Image2Text technology associates images with concepts and enables a host of business opportunities.[5] The technology has implications for augmented reality,[6] a visual technology that experts say will improve when it incorporates computer vision and dynamic mapping of the real world environment.[7] In addition, computer vision technologies, like those guided by Image2Text, have been integrated into self-driving cars to help identify road hazards.[8]

gollark: Yes, I'm sure it devolving into a firefight would really improve the situation.
gollark: I assume people just assumed this sort of thing was too ridiculous to defend against.
gollark: Huh, wow, the article writers are impressively quick.
gollark: I wonder how well-cited that Wikipedia article is.
gollark: They aren't very good weapons for anything but warcrime maximization.

References
  1. Yeung, Ken. "Israel-based Cortica raises $1.5M from Mail.Ru to fund its Image2Text visual search technology". TheNextWeb. Retrieved 20 January 2017.
  2. "Visual Search Leader, Cortica, Secures $6.4 Million in Series B Financing Led by Horizons Ventures; Funding Totals $18M to Date". BusinessWire. Retrieved 20 January 2017.
  3. Chen, David. "Memory Efficient Image Databases for Mobile Visual Search" (PDF). Stanford University. IEEE Journal. Retrieved 20 January 2017.
  4. Bermant, Yoel. "Igal Raichelgauz Raises $20 Million In Series C Funding For Cortica, Image Identification Technology". Jewish Business News. Retrieved 20 January 2017.
  5. "Visual Search Leader, Cortica, Secures $6.4 Million in Series B Financing Led by Horizons Ventures; Funding Totals $18M to Date". BusinessWire. Retrieved 20 January 2017.
  6. Raichelgauz, Igal. "Pokémon Go is nice, but here's what *real* augmented reality will look like". VentureBeat.
  7. Dhillon, Sunny. "Stop referring to Pokémon Go as augmented reality". VentureBeat. Retrieved 20 January 2017.
  8. Els, Peter. "How AI is Making Self-Driving Cars Smarter". RoboticsTrends. Retrieved 20 January 2017.
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