Image recognition is the method of identifying and recognizing objects or qualities in a photo or video. This tool is now developing in remarkable ways that directly affect people in their daily lives. The process of image recognition can now describe, in words, the content of the photo or video by using algorithms written by a collaboration between Google and Stanford University. This procedure works by incorporating two neural networks: image recognition and natural language processing. This means that people will be able to receive more accurate results when searching the internet for particular images and videos. While this development is not perfected, it is an exciting step in advancing image recognition technology.
Slyce, a leading image recognition provider, is using this technology is ways that will simplify and connect the world like never before. Through shopping, advertising, relevancy engines, and social media tags, this company provides intuitive technology that allows customers find exactly what they are looking for. Within the e-commerce system, they are able to locate what someone is looking for just by taking a picture. For example, a woman sees a billboard advertising a new movie, and really likes the shoes that one of the actors is wearing. By taking a photo of the shoes with Slyce, she is able to view that exact pair and/or similar shoes and purchase them. This is a powerful tool that will be used for buying, selling, and advertising internationally. Consumers should expect to see many companies using this in mobile applications in the near future.
What else does the future hold for this branch of technology? As research continues, it’s possible that it can aid the blind and artificial intelligence navigate their environments. Additionally, there are many possibilities for development in surveillance. In the future, the software managing the cameras will go beyond just physical recognition of humans, but also distinguish certain types of behavior, which could potentially alert the authorities automatically. The neural networks used in this kind of technology are inspired by the ways the human brain works, and can additionally be trained to discover patterns in information. Although technology is far behind the human ability to see and comprehend, developers are expectant for the continued improvements in this field.