One of the hardest concepts to grasp when learning about Convolutional Neural Networks for object detection is the idea of anchor boxes. It is also one of the most important parameters you can tune…
If you live in Europe or Japan, it is highly likely that the cut flowers you buy at your local market or in the supermarket are from Kenya. So when the Icelandic volcano disrupted air travel into Europe, the impact was keenly felt here in Africa.
Jeremy is talking about that CNN maybe will take over by the end of the year. What would be the best solution for a time series with parallel parameters that normally use LSTM/GRU to solve before? For example predicting…
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meta description: Making a deep convolutional neural network smaller and faster.
A user-friendly explanation how to compress CNN models - by removing full filters filters from a layer (GPU friendly, unlike sparse layers). L1-norm used for picking candidates for removal. Optimized MobileNet by 25%.
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Y. Kim. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014, October 25-29, 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL, page 1746--1751. (2014)
Y. Kim. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014, October 25-29, 2014, Doha, Qatar, A meeting of SIGDAT, a Special Interest Group of the ACL, page 1746--1751. (2014)
Y. Kim. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), page 1746--1751. Doha, Qatar, Association for Computational Linguistics, (October 2014)
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