transferlearning
There are 67 repositories under transferlearning topic.
jindongwang/transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
freedomofkeima/transfer-learning-anime
Transfer Learning for Anime Characters Recognition
iawooo/ctt
这是一个基于Cloudflare实现的Telegram消息转发机器人，专注于将用户消息安全、高效地转发到后台群组每个用户独立群组中的分话题，直接话题中发送信息而无需再艾特回复，适用于客服、社区管理等场景。
aksh-ai/neuralBlack
A Multi-Class Brain Tumor Classifier using Convolutional Neural Network with 99% Accuracy achieved by applying the method of Transfer Learning using Python and Pytorch Deep Learning Framework
ybendou/easy
This repository is the official implementation Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients.
Mid-Push/Moving-Semantic-Transfer-Network
Tensorflow codes for ICML2018, Learning Semantic Representations for Unsupervised Domain Adaptation
SartajBhuvaji/Brain-Tumor-Classification-Using-Deep-Learning-Algorithms
To Detect and Classify Brain Tumors using CNN and ANN as an asset of Deep Learning and to examine the position of the tumor.
IKKIM00/fall-detection-and-predction-using-GRU-and-LSTM-with-Transfer-Learning
Fall Detection and Prediction using GRU and LSTM with Transfer Learning
Suraj520/CognitiveAnnotationTool
Automatic Annotation tool for labelling images in bulk with their corresponding bounding box annotations.
whitneyli/Domain-Adaptation-Amazon-Reviews-papers
Resources of domain adaptation papers on sentiment analysis that have used Amazon reviews
1146976048qq/IATN
Dataset and code for "Interaction Attention Transfer Network for Cross-domain Sentiment Classification“
hosseinshn/Velodrome
Velodrome combines semi-supervised learning and out-of-distribution generalization (domain generalization) for drug response prediction and pharmacogenomics
leftthomas/PSCapsNet
A PyTorch implementation of Parameter-sharing Capsule Network based on the paper "Evaluating Generalization Ability of Convolutional Neural Networks and Capsule Networks for Image Classification via Top-2 Classification"
shbrief/GenomicSuperSignature
Interpretation of RNAseq experiments through robust, efficient comparison to public databases
LahiRumesh/simple_cnn
Simple CNN is a library that can be used to train and infer CNN models by use of PyTorch and ONNX.
danielfrees/mlpremier
Deep Learning and Transfer Learning Architectures for English Premier League Player Performance Forecasting: CS229 Final Project
yuwei998/Deep_Transfer
transferlearning for small training set object detection
aartighatkesar/Deep-Learning-Fundamentals
Implementation of various basic layers forward and back propagation. CS 231n Stanford Spring 2018: Convolutional Neural Networks for Visual Recognition. Solutions to Assignments
Sanky18/L-T-EduTech-Hackathon-at-SHAASTRA-IITM
Concrete cracking is a major issue in Bridge Engineering. Detection of cracks facilitates the design, construction and maintenance of bridges effectively.
radonys/CV-Assignments
Working repository for Computer Vision course 2018.
samyo00/pyTorch
A collection of code snippets covering the basic fundamentals of PyTorch, including tensors, autograd, neural networks, and optimization.
Hannibal730/KONKUK-Univ_Autonomous-Driving-Competition
건국대학교 주관 행동모사 자율주행 경진대회 1위 (2024.06)
karhong-sam/cracks-image-classification-tensorflow
Apply deep learning to detect and classify cracks. Prior to tensorflow framework and developed a GUI for deployment purposes.
steveee27/Multi-Label-Clothing-Classification-Predicting-Type-and-Color
This project focuses on creating a multi-label classification system to categorize clothing images based on type (T-shirt or Hoodie) and color (Red, Yellow, Blue, Black, White). By leveraging advanced deep learning techniques, this solution aims to streamline product categorization for fashion e-commerce platforms like Matos Fashion.
sunnysoni97/iplantify_droid
Android Application with Tensorflow Backend for Plant Image Classification
Anthony-Antona/Functional-Analysis-and-Transfer-Learning
Final Report - Project of Machine Learning_M2QF_University of Paris Saclay [https://www.universite-paris-saclay.fr/formation/master/mathematiques-et-applications/m2-finance-quantitative]
benjibex/fashion_image_classifer
Fashion Image CNN Classifier using Keras
cchighman/ImageAI-YOLOv3-Fine-Tuning-Vehicle-Classification
Object Detection via pre-trained YOLOv3 is used to detect vehicles from an image. Transfer learning on ResNet-50 outer layers with a two-class dataset trains for 50 epochs. 81% accuracy.
kaledhoshme123/X-ray-Covid-19---Pneumonia-Heat-map
Obtaining a Heat Map of the areas most influential in sorting chest X-ray images.
navanith007/ULMFit-using-pytorch
This repository contains solving of NLP problems using transfer learning
Projects-Developer/Plant-Disease-Detection-Project
A machine learning-based project aimed at detecting and identifying plant diseases from images of affected plants. Plant Disease Detection Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials
ruchithakor/Skin_Cancer_TransferLearning_XAI
Skin cancer classification using Transfer Learning and explainable AI
SkyisjustTheBeginning/breed-identifier
A transfer learning model to identify the breed of a dog from an image.It uses the trained model mobilenet.The modules used are Numpy , PIL , Tensorflow and tensorflow_hub
steveee27/Batik-Motif-Classification-Using-Deep-Learning-and-Transfer-Learning
This project involves the use of deep learning models to classify Indonesian batik motifs. By utilizing deep learning techniques such as Convolutional Neural Networks (CNNs) and Transfer Learning, this project aims to automatically identify three well-known batik motifs: Parang, Mega Mendung, and Kawung.
steveee27/Fruit-Classification-with-VGG-16-Architecture
This project classifies fruit images into four categories: Acai, Acerola, Apple, and Avocado. Using Convolutional Neural Networks (CNN), it predicts fruit types with VGG-16. The model is optimized with data augmentation, dropout, and batch normalization for better performance and accuracy.
xinbinhuang/learn_image_classification
Vancouver School of AI - Image Classification