Computer Vision and Machine Learning
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Updated
May 15, 2018 - Jupyter Notebook
Computer Vision and Machine Learning
Implementation of Show, Attend and Tell
Recognition, Tracking and action discription of objects in video using deep neural networks and image computation algorithms.
Segnet semantic segmentation architecture with VGG-16 implemented with tensorflow
Laplacian of Gaussian, Histogram equalization, SIFT features for scene matching and object recognition, Scene Recognition, Action Recognition
Tensorflow implementation of Very Deep Convolutional Networks for Large-Scale Image Recognition.
Udacity Deep Learning Nanodegree project
A VGG16 model is built to identify free parking lots. Transfer learning is used while training the model.
Implementation of vgg in tensorflow 2.0
Visualization VGG16 models for CIFAR-10 and CIFAR-100 using Keras
A repository for deep learning implementations using TensorFlow and Keras
MNIST classification with deeper CNN models
WebAI Apprication w/VGG16
⚗️ The repository for experiment of Keras, Vgg16 and Fine tuning. The purposes are to practice Fine tuning with "17 flowers" with my own hands and to get to be able to explain Keras, Vgg16 and Fine tuning with my own mouse.
A text/non-text image classifier. Part of software course project.
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