GitHub topics: batch-normalization

Repositories

chefo93/numpy-library

Discover NumPy, the essential library for scientific computing in Python. It offers powerful array operations and seamless integration with C/C++ and Fortran. 🐙✨

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sabin74/image_classification_CIFAR10

This project demonstrates how to build a deep learning image classifier using the CIFAR-10 dataset. Two approaches are implemented: A custom Convolutional Neural Network (CNN) & A transfer learning model using VGG16

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Daisy-butter/Deep_Learning_pj2

This repo contains experiments of models on CIFAR-10 and the discussion on BN.

Language: Python - Size: 12.7 KB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 0 - Forks: 0

MorvanZhou/PyTorch-Tutorial

Build your neural network easy and fast, 莫烦Python中文教学

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ChanchalKumarMaji/Coursera-Deep-Learning-Specialization-deeplearning.ai

[Coursera] Deep Learning Specialization on Coursera

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Assem-ElQersh/AlexNet-VGG-CIFAR10-Comparison

Comparative analysis of AlexNet and VGG architectures trained on the CIFAR-10 dataset. The project explores differences in model design, feature extraction capabilities, and performance metrics across different neural network architectures.

Language: Jupyter Notebook - Size: 3.68 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

mbeps/custom-neural-network-classifier

The project implements a neural network classifier with advanced techniques like batch normalisation, dropout, and gradient clipping to control Pacman's movements based on the game state. This is a coursework for the Machine Learning (6CCS3ML1) module for King's College London.

Language: Python - Size: 294 KB - Last synced at: 6 days ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

anish-lakkapragada/SeaLion

The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.

Language: Python - Size: 37.9 MB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 333 - Forks: 35

hwalsuklee/tensorflow-mnist-cnn

MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.

Language: Python - Size: 168 MB - Last synced at: about 2 months ago - Pushed at: almost 7 years ago - Stars: 202 - Forks: 96

imedslab/pytorch_bn_fusion 📦

Batch normalization fusion for PyTorch. This is an archived repository, which is not maintained.

Language: Python - Size: 54.7 KB - Last synced at: 6 days ago - Pushed at: about 5 years ago - Stars: 197 - Forks: 29

stevenobadja/math_object_detection

An image recognition/object detection model that detects handwritten digits and simple math operators. The output of the predicted objects (numbers & math operators) is then evaluated and solved.

Language: Python - Size: 413 MB - Last synced at: 21 days ago - Pushed at: about 7 years ago - Stars: 66 - Forks: 19

lyttonhao/Neural-Style-MMD

MXNet Code For Demystifying Neural Style Transfer (IJCAI 2017)

Language: Python - Size: 5.52 MB - Last synced at: 2 months ago - Pushed at: about 8 years ago - Stars: 84 - Forks: 22

rezakj/iCellR

Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).

Language: R - Size: 68.2 MB - Last synced at: about 2 months ago - Pushed at: 12 months ago - Stars: 122 - Forks: 19

hwalsuklee/tensorflow-mnist-MLP-batch_normalization-weight_initializers

MNIST classification using Multi-Layer Perceptron (MLP) with 2 hidden layers. Some weight-initializers and batch-normalization are implemented.

Language: Python - Size: 1.62 MB - Last synced at: 2 months ago - Pushed at: over 8 years ago - Stars: 55 - Forks: 17

ArtZaragozaGitHub/NN--P4_Predicting_Customers_Likely_to_Abandon_Bank_Services

Analyze the customer data, build a neural network to help the operations team identify the customers that are more likely to churn, and provide recommendations on how to retain such customers

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apple/ml-tune-mode-convbn

Tune-Mode ConvBN Blocks For Efficient Transfer Learning

Language: Python - Size: 702 KB - Last synced at: about 2 months ago - Pushed at: almost 2 years ago - Stars: 17 - Forks: 1

AdityaDutt/Audio-Classification-Using-Wavelet-Transform

Classifying audio using Wavelet transform and deep learning

Language: Python - Size: 19.8 MB - Last synced at: 2 months ago - Pushed at: almost 4 years ago - Stars: 35 - Forks: 6

ChaitanyaC22/Deep_Learning_Hand_Gesture_Recognition_Project

The objective of this project is to recognize hand gestures using state-of-the-art neural networks.

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arjuntheprogrammer/TheSchoolOfAI

Projects for The School of AI

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pngo1997/Convolutional-Neural-Network-Intel-Image-Classification

Experiments with Convolutional Neural Networks (CNNs) to classify images from the Intel Image Classification dataset.

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ashithapallath/facemaskdetection-using-cnn

This project implements a CNN-based Face Mask Detection Model to classify images as with mask or without mask. Trained on a labeled dataset, the model achieves 90% accuracy, making it suitable for real-world applications like public safety monitoring.

Language: Jupyter Notebook - Size: 501 KB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 0 - Forks: 0

26hzhang/AmusingPythonCodes

Interesting python codes to tackle simple machine/deep learning tasks

Language: Python - Size: 1.07 GB - Last synced at: 2 months ago - Pushed at: over 2 years ago - Stars: 34 - Forks: 27

marcvidalbadia/functional-whitening

Supplementary Online Material for M. Vidal & A. M. Aguilera. Novel whitening approaches in functional settings. Stat, 12(1), e516.

Language: R - Size: 1.77 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 3 - Forks: 0

fatimagulomova/deep-learning-course

Deep Learning Courses

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himanshumahajan138/TransferVision

Transfer learning for image classification using pre-trained models like ResNet50, ResNet100, EfficientNetB0, and VGG16 in Keras. Fine-tunes the last layers, applies image augmentation, and evaluates with Precision, Recall, AUC, F1 score, and early stopping for improved performance.

Language: Jupyter Notebook - Size: 1.41 MB - Last synced at: 21 days ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

AdityaDutt/Bird-Song-Classification

Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.

Language: Python - Size: 2.83 MB - Last synced at: 2 months ago - Pushed at: almost 4 years ago - Stars: 17 - Forks: 8

VITA-Group/BNN_NoBN

[CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang

Language: Python - Size: 310 KB - Last synced at: 2 months ago - Pushed at: over 3 years ago - Stars: 57 - Forks: 10

sayakpaul/Training-BatchNorm-and-Only-BatchNorm

Experiments with the ideas presented in https://arxiv.org/abs/2003.00152 by Frankle et al.

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VITA-Group/Sandwich-Batch-Normalization

[WACV 2022] "Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity" by Xinyu Gong, Wuyang Chen, Tianlong Chen and Zhangyang Wang

Language: Python - Size: 21.9 MB - Last synced at: 2 months ago - Pushed at: over 3 years ago - Stars: 50 - Forks: 5

parasdahal/deepnet

Educational deep learning library in plain Numpy.

Language: Python - Size: 40 KB - Last synced at: 7 months ago - Pushed at: about 3 years ago - Stars: 322 - Forks: 83

akthammomani/Casual_Conversation_Chatbot

Build a Multi-turn Conversations Chit-Chat Bot

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csm9493/TaskBalancedBN

Official Code of Rebalancing Batch Normalization for Exemplar-based Class-Incremental Learning (CVPR 2023)

Language: Python - Size: 342 KB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

priyadarshighosh/ANN_Everyday

Everything about Artificial Neural Network from Basic to Adavnced

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Erick-Helmeczi/Metabolomic-Batch-Correction

An Interactive R Markdown File for Metabolomic QC-Based Batch Corrections

Size: 55.7 KB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

philipperemy/keras-mode-normalization

Keras Implementation of Mode Normalization (Lucas Deecke, Iain Murray, Hakan Bilen, 2018)

Language: Python - Size: 240 MB - Last synced at: 14 days ago - Pushed at: about 5 years ago - Stars: 5 - Forks: 1

ishreya09/Skin-Cancer-Detection

Developed a CNN model to classify skin moles as benign or malignant using a balanced dataset from Kaggle, achieving a test accuracy of 81.82% and an AUC of 89.06%. Implemented data preprocessing by resizing images to 224x224 pixels and normalizing pixel values, enhancing model performance and stability.

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saminheydarian/DeepLearning_Course_2021

Deep Learning Course | Home Works | Spring 2021 | Dr. MohammadReza Mohammadi

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hugohiraoka/Plant_Seedlings_Images_Classification

A CNN model to identify images of plant seedlings.

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adityab/CrossQ

Official code release for "CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity"

Language: Python - Size: 5.7 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 44 - Forks: 2

SarveshChandra/Machine-Learning-and-Artificial-Intelligence-Case-Studies

AIML Projects

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mindee/Problem-of-BatchNorm

Playground repository to highlight the problem of BatchNorm layers for an blog article

Language: Python - Size: 7.81 KB - Last synced at: 3 months ago - Pushed at: over 3 years ago - Stars: 5 - Forks: 0

AdalbertoCq/Deep-Learning-Specialization-Coursera

Deep Learning Specialization courses by Andrew Ng, deeplearning.ai

Language: Jupyter Notebook - Size: 122 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 249 - Forks: 256

AdalbertoCq/NeuralNetwork

Neural Network implementation in Numpy and Keras. Batch Normalization, Dropout, L2 Regularization and Optimizers

Language: Python - Size: 8.01 MB - Last synced at: about 1 year ago - Pushed at: about 6 years ago - Stars: 16 - Forks: 6

karoly-hars/GAN_image_colorizing

Image colorization with generative adversarial networks on the CIFAR10 dataset.

Language: Python - Size: 1.72 MB - Last synced at: about 2 months ago - Pushed at: over 5 years ago - Stars: 11 - Forks: 4

harinik05/LeukoDif

Denoising diffusion medical model (DDMM) for diagnosis of Acute Lymphoblastic Leukemia

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abaybektursun/why-batchNorm-works

Source Code For: Why Does Batch Normalization Work?

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somjit101/MNIST-Classification-Tensorflow

A simple study on how to use Tensorflow platform (without Keras) for a simple number classification task using a Neural Network.

Language: Jupyter Notebook - Size: 390 KB - Last synced at: 4 months ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0

soloice/mnist-bn

Using slim to perform batch normalization

Language: Python - Size: 718 KB - Last synced at: about 1 year ago - Pushed at: over 6 years ago - Stars: 60 - Forks: 18

cvjena/cnn-models

ImageNet pre-trained models with batch normalization for the Caffe framework

Language: Python - Size: 3.36 MB - Last synced at: over 1 year ago - Pushed at: over 7 years ago - Stars: 361 - Forks: 161

twke18/Adaptive_Affinity_Fields 📦

Adaptive Affinity Fields for Semantic Segmentation

Language: Python - Size: 2.63 MB - Last synced at: about 1 year ago - Pushed at: almost 7 years ago - Stars: 260 - Forks: 62

vicaaa12/Deep-Neural-Networks

Neural Network

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manashpratim/Deep-Learning-From-Scratch

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kiwi12138/RealisticTTA

Official repository for AAAI2024 paper <Unraveling Batch Normalization for Realistic Test-Time Adaptation>.

Language: Python - Size: 519 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 1

srinadhu/convolutional_nn

Implemented fully-connected DNN of arbitrary depth with Batch Norm and Dropout, three-layer ConvNet with Spatial Batch Norm in NumPy. The update rules used for training are SGD, SGD+Momentum, RMSProp and Adam. Implemented three block ResNet in PyTorch, with 10 epochs of training achieves 73.60% accuracy on test set.

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RimTouny/Weed-Species-Classification-and-Bounding-Box-Regression

Leveraging advanced image processing and deep learning, this project classifies plant images using a subset of the Plant Seedlings dataset. The dataset includes diverse plant species captured under varying conditions. This project holds significance within my Master's in Computer Vision at uOttawa (2023).

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Cyril9227/Keras_AttentiveNormalization

Unofficial Keras implementation of the paper Attentive Normalization.

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Cyril9227/Keras_IEBN

Unofficial Keras implementation of the paper Instance Enhancement Batch Normalization.

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mohadeseh-ghafoori/Coursera-Deep-Learning-Specialization

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MattMoony/convnet_mnist

Simple convolutional neural network (purely numpy) to classify the original MNIST dataset. My first project with a convnet. 🖼

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Yuanzhe-Jia/BNNAS Fork of bychen515/BNNAS

BN-NAS: Neural Architecture Search with Batch Normalization

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tooth2/Traffic-Light-Classification

A open-cv and CNN(Tensorflow) implementation to detect Traffic light (red, yellow, green) state

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tooth2/Celeb-Face-Generation

A PyTorch Implementation of DCGAN on a dataset of celebrity faces.

Language: Jupyter Notebook - Size: 214 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

tooth2/House-Number-Recognition

Using DCGAN, detect and recognize house number from google street view

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Connor-Shen/Exploration-on-Batch-Normalization

In this PJ I build a simple Conv2d network and implement some beneficial modifications based on it. Meanwhile, by researching into the BatchNorm algorithm, I verify its benefits on a variety of procedures.

Language: Python - Size: 5.66 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

sahildigikar15/Different-CNN-Architectures-on-MNIST-dataset-

Experimented with different architectures and kernels on MNIST dataset using Convolutional Neural Networks.

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sahildigikar15/MLP-Architetures-on-MNIST-dataset

Experimented with different architectures on MNIST dataset using MLPs with different dropouts.

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eigenfoo/batch-renorm

A Tensorflow re-implementation of batch renormalization, first introduced by Sergey Ioffe.

Language: Python - Size: 752 KB - Last synced at: 2 months ago - Pushed at: over 4 years ago - Stars: 13 - Forks: 0

osu-cvl/revisiting-bn-init

Code for "Revisiting Batch Norm Initialization".

Language: Python - Size: 19.5 KB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 11 - Forks: 1

somefunAgba/deeplearningWithMatlabinPy

Investigating the Behaviour of Deep Neural Networks for Classification

Language: Python - Size: 1.15 MB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 0

tamakoji/pytorch-syncbn

Synchronized Multi-GPU Batch Normalization

Language: Python - Size: 20.5 KB - Last synced at: over 1 year ago - Pushed at: about 6 years ago - Stars: 223 - Forks: 22

snrazavi/Machine-Learning-in-Python-Workshop

My workshop on machine learning using python language to implement different algorithms

Language: Jupyter Notebook - Size: 23 MB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 111 - Forks: 63

Justsecret123/One-Piece-Image-Classifier

A quick image classifier trained with manually selected One Piece images.

Language: Jupyter Notebook - Size: 83.3 MB - Last synced at: 3 months ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 1

Baksonator/fashionMNIST-classifier Fork of raf-bsn/ML-project2

Convoluted Neural Network for classifying the FashionMNIST data set. Recognition of multiple clothing objects on the same picture with noise using the trained model and OpenCV.

Language: Python - Size: 66.5 MB - Last synced at: almost 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0

Hsnmhmd/Vision

in this repo, you will find implementation of various classification models, data augmantation ,cnn designing and model reguralization

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hugohiraoka/Bank_Customer_Churn_Prediction

Model to predict bank customer churn

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ilango100/batch_norm

My experiments with Batch Normalization

Language: Jupyter Notebook - Size: 389 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 2

Si-ddhartha/BatchNorm_Before_vs_After

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hwixley/MLP-coursework2-report

Machine Learning Practical - Coursework 2 Report: Analysing problems with the VGG deep neural network architectures (with 8 and 38 hidden layers) on the CIFAR100 dataset by monitoring gradient flow during training. And exploring solutions using batch normalization and residual connections.

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hwixley/MLP-coursework2

Machine Learning Practical - Coursework 2: Analysing problems with the VGG deep neural network architectures (with 8 and 38 hidden layers) on the CIFAR100 dataset by monitoring gradient flow during training. And exploring solutions using batch normalization and residual connections.

Language: Python - Size: 3.37 GB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0