TensorFlow version of SqueezeNet with converted pretrained weights
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Updated
Mar 11, 2017 - Python
TensorFlow version of SqueezeNet with converted pretrained weights
A pre-trained VGG for fine-tuning and usage in other networks
Keras code and weights files for popular deep learning models.
A native Tensorflow implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions (2016). Optionally uses the pretrained weights by the authors.
Experiment with pre-training spaCy
Implementation of object detection using yoloV3 model, keras and pretrained model's weights.
Uses a Pretrained Network (using Google's Deepmind) to generate images.
Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights.
pytorch implementation of several CNNs for image classification
A Pytorch implementation of the 2017 Huang et. al. paper "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization"
An implementation of MobileNetV3 with pyTorch
Pretrained Efficient DenseNet Model
A Deep Learning based project for colorizing and restoring old images and videos!
FER and Gender Recognition.
In this assignment I have to build a Mask R-CNN based keypoint detector model using Detectron2. Detectron2 was written in PyTorch and contains many state-of-the-art obejct detection models with pretrained weights.
A deep learning model built to detect cataract in human eyes using the VGG-19 pretrained weights
Design of several classifiers to discriminate between calcification and masses, as well as, benign and malignant ones of mammography films.
AI Models Implementation on Tensorflow
Pre-trained NFNets with 99% of the accuracy of the official paper "High-Performance Large-Scale Image Recognition Without Normalization".
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