TensorFlow based mobile neural network model resources
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Updated
Sep 10, 2017
TensorFlow based mobile neural network model resources
implementation of Inflated 3D ConvNet in TensorFlow
TensorFlow implementation of GoogLeNet.
Realtime Face Recognition using FaceNet architecture
Implementation of various state-of-the-art architectures in Tensorflow, Keras and Python
使用TensorFlow自己搭建一些经典的CNN模型,并使用统一的数据来测试效果。
Flowers Recognition with transfer learning
This repository is the implementation of several famous convolution neural network architecture with Keras. (Resnet v1, Resnet v2, Inception v1/GoogLeNet, Inception v2, Inception v3))
Computer Vision .Libraries used matplot, numpy, openCV, mazelib standard machine learning libs you know dude
Create your own databse, compile tripletloss with pre-trained FaceNet model, run real-time face recognition on local host
My PyTorch implementation of CNNs. All networks in this repository are using CIFAR-100 dataset for training.
Summary & Implementation of Deep Learning research paper in Tensorflow/Pytorch.
This project was completed under the course Deep Learning(CSE674) at University at Buffalo.
TensorFlow Lite classification on a bare Raspberry Pi 4 with 64-bit OS at 23 FPS
TensorFlow Lite classification on a bare Raspberry Pi 4 at 33 FPS
Models Supported: Inception [v1, v2, v3, v4], SE-Inception, Inception_ResNet [v1, v2], SE-Inception_ResNet (1D and 2D version with DEMO for Classification and Regression)
Music emotions and themes classifier app could recognize 56 classes using three trained models (based on ResNet50, InceptionNetV2, EfficientNetB3), applying the transfer learning approach.
PyTorch implements `Rethinking the Inception Architecture for Computer Vision` paper.
Tensorflow Implementation of FaceNet: A Unified Embedding for Face Recognition and Clustering to find the celebrity whose face matches the closest to yours.
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