There are 1 repository under svhn-dataset topic.
Implemented digit detector in natural scene using resnet50 and Yolo-v2. I used SVHN as the training set, and implemented it using tensorflow and keras.
Official adversarial mixup resynthesis repository
A pip-installable evaluator for GANs (IS and FID). Accepts either dataloaders or individual batches. Supports on-the-fly evaluation during training. A working DCGAN SVHN demo script provided.
This project is a PyTorch implementation that uses deep CNN to recognize multi-digit numbers using the SVHN dataset derived from Google Street View house numbers, each picture contains a set of numbers from 0 to 9, the model is tested to have 89% accuracy.| 使用深度卷积神经网络从街景图像中识别多位数门牌号的PyTorch实现方案,使用的数据集为SVHN,来源于谷歌街景门牌号码,每张图片中包含一组0-9的阿拉伯数字,经测试精确度可达89%
Pytorch implementation of homework 2 for VRDL course in 2021 Fall semester at NYCU.
An Exploration of Machine Learning Methods on SVHN Dataset
An implementation of a Convolutional VAE on the SVHN dataset.
A project constructing an image representation model via unsupervised and self-supervised learning.
Numerical Digit Detection and Classification on SNVH Dataset
Second Assignment in 'Practical topics in Machine Learning' course by Dr. Kfir Bar at Bar-Ilan University
Convolutional Neural Network created using Keras with tensorflow backend. Machine learning model used to predict the digit on a photo.
Selected Topics in Visual Recognition using Deep Learning, NYCU. CodaLab competition - Object Detection
Using attention for sequence classification for multi-character prediction
Solutions for Advanced Image Analysis course assignments, featuring model designs for image summation and generation with MNIST, and style transfer using CycleGAN with MNIST and SVHN datasets.
Image Recognition Using both methods convolutional neural Networks (CNN) and Artificial Neural Networks (ANN) to check how well both model perform
The goal of this project is to develop an end-to-end workflow for building, training, validating, evaluating and saving a neural network that classifies a real-world image into one of ten classes
Implementation of DCGAN on the Street View House Numbers (SVHN) dataset.
Domain Adaptation for digits classification using Deep Reconstruction-Classification Network
We implement a conditional Deep Convolutional Generative Adversarial Network (DCGAN) sampling high-quality Street View House Numbers (SVHN), conditioned on an embedding of a desired label.
This repository houses a series of convolutional neural networks and performance benchmarks developed as part of UMass Dartmouth's CIS465 Topics in Computer Vision course.
This Computer Vision project is about training our model to accurately identify the House Numbers that are captured by the Google Street View. I have used the SVHN dataset to accomplish this task. Leaveraging some refined structure of the Layers of our Network, I was able to acheive good accuracy.
gan that tries to generate samples from the svhn database
Implementation of a Quantized Neural Network with low bitwidth of weights, activations and gradients.
Domain adversarial network trained on MNIST-M, SVHN, and USPS
Domain Adaptation With Domain-Adversarial Training of Neural Networks