AI News, BOOK REVIEW: NIPS Proceedingsβ
- On 3. december 2018
- By Read More
Part of: Advances in Neural Information Processing Systems 27 (NIPS 2014) This paper investigates how to extract objects-of-interest without relying on hand-craft features and sliding windows approaches, that aims to jointly solve two sub-tasks: (i) rapidly localizing salient objects from images, and (ii) accurately segmenting the objects based on the localizations.
We present a general joint task learning framework, in which each task (either object localization or object segmentation) is tackled via a multi-layer convolutional neural network, and the two networks work collaboratively to boost performance.
- On 22. september 2020
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You can directly support Crash Course at Subscribe for as little as $0 to keep up with everything we're doing. Also, if you can afford to pay a little every..
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