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cifar10-vgg16 Description. CNN to classify the cifar-10 database by using a vgg16 trained on Imagenet as base. The approach is to transfer learn using the first three blocks (top …
we can see that I get 92.05% with a constant learning rate instead of 80.9% using learning rate decay. I added 2 layers with ReLU activation and 1 layer for softmax.
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Python · cifar10, [Private Datasource] VGG16 with CIFAR10. Script. Data. Logs. Comments (0) No saved version. When the author of the notebook creates a saved version, it will appear here. We …
VGG16 and VGG19 caffe net. Uses the VGG16 and VGG19 nets from the modelzoo. Minor changes in the *.prototxt to adapt it to the new caffe version. See net.ipynb.
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I'm trying to train the mobileNet and VGG16 models with the CIFAR10-dataset but the accuracy can't get above 9,9%. I need it with the completly model (include_top=True) and …
95.47% on CIFAR10 with PyTorch Topics. pytorch Resources. Readme License. MIT license Stars. 4.9k stars Watchers. 80 watching Forks. 1.9k forks Releases No releases …
CIFAR-10 is a well-understood dataset and widely used for bench-marking computer vision algorithms. The problem is effectively “solved”. It is relatively easy to achieve …
Caffe. Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research ( BAIR) and by community contributors. Yangqing Jia …
Hello, I’m new to PyTorch and try to train a model. The network needs to be defined in Sequential and I want to train it on CIFAR10. Unfortunately, something isn’t working correctly, …
I am currently trying to classify cifar10 data using the vgg16 network on Keras, but seem to get pretty bad result, which I can't quite figure out... The vgg16 is designed for …
I was working on fine-tuning examples (currently on VGG16). I want to train the CIFAR10 dataset with VGG16 but the expected input dimensions are greater than 48x48px …
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