Feed your own image data to a pre-trained network by tensorflow
-
Updated
Nov 29, 2018 - Python
#
cnn-training
Here are 5 public repositories matching this topic...
TensorFlow (Keras) implementation of MobileNetV3 and its segmentation head
docker computer-vision deep-learning neural-network notebook makefile tensorflow cnn segmentation jupyter-notebooks semantic-segmentation loss-functions augmentation cnn-training cnn-segmentation person-segmentation mobilenetv3 cnn-architectures
-
Updated
Jul 6, 2023 - Python
Code for the paper "Training CNNs with Selective Allocation of Channels" (ICML 2019)
-
Updated
May 14, 2019 - Python
QuickCNN is high-level library written in Python, and backed by the Keras, TensorFlow, and Scikit-learn libraries. It was developed to exercise faster experimentation with Convolutional Neural Networks(CNN). Majorly, it is intended to use the Google-Colaboratory to quickly play with the ConvNet architectures. It also allow to train on your local…
deep-learning tensorflow keras image-classification tensorboard transfer-learning convolutional-neural-network fine-tuning-cnns cnn-training bottleneck-features sklearn-library google-colaboratory
-
Updated
Dec 29, 2018 - Python
low level tensorflow implementation of squeezenet
python deep-learning tensorflow cnn tensorboard convolutional-neural-networks squeezenet cnn-model cnn-training
-
Updated
Feb 14, 2018 - Python
Improve this page
Add a description, image, and links to the cnn-training topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the cnn-training topic, visit your repo's landing page and select "manage topics."