I was going through a brief introduction on deep learning prepared by Mathworks. It gave me an idea that deep learning is mainly useful for image recognition given the fact that there's is only one well-trained deep learning network (AlexNet) available and that too is for image recognition.
You can easily google out an answer with the key words deep learning industry. Here is an example:
Conference Paper Deep Learning in the Automotive Industry: Applications and Tools
https://www.techemergence.com/machine-learning-in-manufacturing/
Dear Sergei, I know I could have used google scholar. But sometimes the expert advice and useful insights can guide us in the right direction. Thanks a lot for sharing that publication, it is very informative.
Please use this link to go through this article , it elucidates some 30 astounding applications ( of recent origin) of deep learning:
http://www.yaronhadad.com/deep-learning-most-amazing-applications/
In video compression standard (i.e. the next generation video compression standard, H.266), we started experiment deep learning for in-loop filter, fast mode prediction, interpolation, prediction, etc.
Example like:
CNN-based driving of block partitioning for intra slices encoding at
http://phenix.it-sudparis.eu/jvet/doc_end_user/documents/10_San%20Diego/wg11/JVET-J0034-v1.zip
- Badges
- Science topic
- Similar topics
- Computer Science
- Images