How can I use Faster Region based Convolutional Neural Network (Faster R-CNN) for Real-Time Object Detection ?d
I have to generate a logic using deep learning with MATLAB.
Dear Sir
Please follow the below link for Matlab code and work done by a researcher on your topic
https://www.cs.toronto.edu/~kriz/
https://code.google.com/archive/p/cuda-convnet/
Hope these links will help
Hi,
I think faster R-CNN is quite slow. It's only 5 fps.
If you want the real-time object detection you can use YOLO or SSD method.
SSD: https://arxiv.org/abs/1512.02325
YOLO: https://pjreddie.com/darknet/yolo/
Hope it helps you.
Have you tried transforming the datasets into a data graph where each element is a tensor, then pre-process the tensors using a twisted manifold? If that is works then try the fnn algorithm as feed forward back prop. model.
I would suggest trying the new Data Stax Cassandra offering (trial version) or the community version. You would normally start cassandra with the - g option. This worked pretty well for CERN's LHC project.
Your problem then moves into the data collection systems where there might be some economizing algorithms that may be useful. Check your model's ability to us multi-core computing techniques.
Good fortune to your and your team!
I am presently working on real time monitoring of cow in an unconstrained environment....any help?
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