Google AI new skills! It can know if you like an image
This article is produced by NetEase Smart Studio (public number smartman 163). Focus on AI and read the next big era! [NetEase smart news December 25 news] Google's artificial intelligence researchers recently demonstrated a new training method that allows computers to understand why some images are more beautiful than other images. Traditionally, machines use basic categories—for example, to determine if an image has a "cat." New research shows that artificial intelligence can now score image quality regardless of category. This process is called Neural Image Evaluation (NIMA), which uses deep learning training convolutional neural networks (CNN) to predict the image's rating. According to a white paper published by the researchers: "Our approach differs from other approaches because we use convolutional neural networks to predict the distribution of human opinion scores. Our results network can not only be used to reliably score images, but also Human perception is highly relevant and can also help to adjust and optimize photo editing/enhancement algorithms in the photography channel." The NIMA model avoids the traditional method and uses a 10-point scale. The machine checks the image for specific pixels and overall aesthetics. Then it decides how big a particular rating may be chosen by one person. Basically, artificial intelligence tries to guess how much a person likes this picture. This does not give the machine the ability to perceive or think, but it may make the computer a better artist or curator. This process may be applied to find the best pictures. If you are the kind of person who takes 20 or 30 pictures each time, this can save you a lot of space in order to ensure that you have the best picture. Assume that with the click of a button, the AI ​​can view all the pictures in the store and determine which pictures are similar, then keep the best and delete the rest. According to a recent article in the Google Research Blog, NIMA can also be used to optimize image settings to produce perfect results: "We observed that the contrast adjustments made by the NIMA scores can improve the aesthetic score of the benchmark. Therefore, our model can guide a deep CNN filter to find near-ideal settings for its parameters, such as brightness, highlights, and shadows." Creating a neural network that understands image quality almost as much as humans does not seem revolutionary, but there are many computer applications that have vision like humans. In order for AI to perform tasks in the real world, such as driving a car safely without human help, it must be able to "see" and understand its environment. NIMA, and projects like it, are laying the foundation for future full-featured machines. (Selected from: thenextweb Author: Tristan Greene compile: NetEase see foreign intelligence platform compiler revision: nariiy) Pay attention to NetEase smart public number (smartman163), obtain the latest report of artificial intelligence industry. Capacitor for Electric Furnace Capacitor For Electric Furnace, commonly referred to as capacitors, are capacitors, expressed in the letter C.Definition 1: a capacitor, as the name implies, is a "charging vessel", a device that holds charge.Capacitor.Capacitors are one of the most widely used electronic components in electronic equipment. They are widely used in the fields of interleaving, coupling, bypass, filtering, tuning circuit, energy conversion and control.Definition 2: a capacitor consisting of any two conductors (including wires) that are insulated from each other and are very close together.
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