Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
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Updated
Feb 22, 2024 - Python
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
🙄 Difficult algorithm, Simple code.
food image to recipe with deep convolutional neural networks.
I transfer the backend of yolov3 into Mobilenetv1,VGG16,ResNet101 and ResNeXt101
ImageNet pre-trained models with batch normalization for the Caffe framework
Deep learning codes and projects using Python
Holistically-Nested Edge Detection
Video Classification using 2 stream CNN
tensorflow implementation of Grad-CAM (CNN visualization)
A neural network to generate captions for an image using CNN and RNN with BEAM Search.
SFD implement with pytorch
Apparel detection using deep learning
Class-Weighted Convolutional Features for Image Retrieval (BMVC 2017)
Accelerate Neural Net Training by Progressively Freezing Layers
Keras code and weights files for the VGG16-places365 and VGG16-hybrid1365 CNNs for scene classification
Implemention of FCN-8 and FCN-16 with Keras and uses CRF as post processing
The purpose of this program is for studying. Using tensorflow trains the vgg16 and recognizes only two kinds of picture(cat and dog).
A Single Shot MultiBox Detector in TensorFlow
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