Computers and data networks pdf10/30/2023 Although increased model size and computational cost tend to translate to immediate quality gains for most tasks (as long as enough labeled data is provided for training), computational efficiency and low parameter count are still enabling factors for various use cases such as mobile vision and big-data scenarios. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains in various benchmarks. Download a PDF of the paper titled Rethinking the Inception Architecture for Computer Vision, by Christian Szegedy and 4 other authors Download PDF Abstract:Convolutional networks are at the core of most state-of-the-art computer vision solutions for a wide variety of tasks.
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