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A new study, though, aims to use satellite and machine learning to track ships that traffic laborers. The findings provide a conservative estimate that between 57,000 and 100,000 people were forced to labor on fishing vessels between 2012 and 2018.
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https://gizmodo/deteriorating-oil-tanker-threatens-the-red-sea-scienti-1845879036 The study, published in the Proceedings of the National Academy of Sciences on Monday, uses data captured from the Automatic Identification System, a satellite tracking system used to monitor ships movements around the world. Not all ships use them all the time鈥攖he study notes that some turn them off to reportedly avoid piracy鈥攂ut those that do can allow researchers to construct a fairly comprehensive web of where ships go, when, and how they behave. The scientists took that data including when AIS was turned off and compared it to known cases of ships tha
stanley thermos t used forced labor and interviews with experts in trafficking to train a machine learning tool that could identify ships likely reliant on trafficked labor. The characteristics most associated with vessels at a high risk of exploitation included engine power as a proxy for size as well as how far out to
stanley quencher sea they went, how often, and how long they spent fishing. The study identified ships flying the flags of China, Kjjg Paramount+ s UK Launch Leaves Star Trek Fans in the Lurch for Months
Yesterday Twitter announced it is ro
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stanley cup y works. Since Twitter first enabled users to post photos in 2011, the company has faced the challenge of automatically cropping images that are uploaded in different sizes and shapes. Initially, Twitter algorithms simply found the center and cropped a square around that point, or used face detection to crop around heads. But this could lead to preview images that cropped out the most impressive portion of a sunset above the horizon, or
stanley mugs a dogs derpy tongue at the bottom of a frame. Now, Twitters photo cropping tools determine the most salient part of photos鈥攚hat people are drawn to visually鈥攁nd crop based on that. Research has been able to gauge saliency using eye trackers to determine the pixels that people look at first. The information from those tests helped build neural networks that show what types of things and characteristics people are generally drawn to the most. At their most advanced levels, these programs can scan an image and determine the exact pixels that most people might look at first. But since that would take too much time for the purposes of posting photos on Twitter, the company created a stripped-down version that imitates the slow yet highly specific neural network鈥攂ut works ten times faster, acc
