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Section II discusses related work and our contributions. The proposed LHBDC framework is presented in Section III. Experimental results are shown in Section IV. Finally, Section V concludes the paper. R-D optimized image compression. Existing end-to-end learned video codecs replace the functional blocks in a standards-based video codec with deep networks, such that different networks for key frame compression, motion estimation, motion compensation, motion vector compression, and residual compression are optimized together based on a single R-D loss. These end-to-end learned video codecs use fully convolutional and/or recurrent architectures, and they can be employed for sequential or bi-directional motion-compensated video coding. In the following, we review selected works that define the state of the art in learned video compression. For motion compensation, DVC employs flow-based back-warping, which inevitably produces artefacts in areas with fast motion or occlusion. This problem is alleviated by introducing a motion compensation post-processing network. DVC by scale-space warping, where a scale channel is added to the flow-field tensor as a third dimension. For example, a sentence like, "This semester is really taking a toll on me" could register as a hit. To train the algorithm, the team first took a selection of posts from mental health subreddits as well as a control group of posts from subreddits unrelated to mental health. They used a method called inductive transfer learning to train the algorithm. This is a type of machine learning that involves storing knowledge gained by solving one type of problem. Then applying that knowledge to a different but related problem. Using their algorithm, the team developed a metric they called the Mental Well-being Index or MWI. A high MWI meant the student body posted about mental health issues less frequently on their university's subreddit, while a school with a low MWI indicated a higher concentration of such posts. According to the researchers, their algorithm was more than 90 percent accurate in identifying posts on subreddits that contained language indicating a student was suffering from some sort of mental health issue. 7 maravillas del mundo antiguo

















































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