提供了一个街景字符编码识别方案以供参考

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.

gan that tries to generate samples from the svhn database

Domain adversarial network trained on MNIST-M, SVHN, and USPS

Implementation of DCGAN on the Street View House Numbers (SVHN) dataset.

Implementation of a Quantized Neural Network with low bitwidth of weights, activations and gradients.

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.

Domain Adaptation for digits classification using Deep Reconstruction-Classification Network

Convolutional Neural Network created using Keras with tensorflow backend. Machine learning model used to predict the digit on a photo.

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.

An implementation of a Convolutional VAE on the SVHN dataset.

Second Assignment in 'Practical topics in Machine Learning' course by Dr. Kfir Bar at Bar-Ilan University

Domain Adaptation With Domain-Adversarial Training of Neural Networks

Image Recognition Using both methods convolutional neural Networks (CNN) and Artificial Neural Networks (ANN) to check how well both model perform

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.

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.

Pytorch implementation of homework 2 for VRDL course in 2021 Fall semester at NYCU.

Building a CNN model using SVHN dataset