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NeuralVision is a machine vision platform at the forefront of deep learning and artificial intelligence-like abilities applied to the industrial inspection space. For the first time companies are able to have total control of the performance of their machine vision systems and not be dependent on external vision experts to make changes or incorporate new product lines. Traditional machine vision is highly dependent on having a controlled environment, rigid positional tolerances, and ultimately the skill of the vision programmer. It is up to engineers to come up with every algorithm required to inspect a part from measurements to color to correct locations and everything in between. NeuralVision from Cyth Systems was designed to allow a person with no machine vision experience to inspect and classify products. Machine vision systems traditionally work by having an experienced programmer choose one of many analysis algorithms to apply to an image.

Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases. With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required.