Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
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Jan 10, 2022 - Python
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Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Transfer Learning for Anime Characters Recognition
Tensorflow codes for ICML2018, Learning Semantic Representations for Unsupervised Domain Adaptation
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
Automatic Annotation tool for labelling images in bulk with their corresponding bounding box annotations.
Resources of domain adaptation papers on sentiment analysis that have used Amazon reviews
Dataset and code for "Interaction Attention Transfer Network for Cross-domain Sentiment Classification“
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"
Velodrome combines semi-supervised learning and out-of-distribution generalization (domain generalization) for drug response prediction and pharmacogenomics
Fall Detection and Prediction using GRU and LSTM with Transfer Learning
Interpretation of RNAseq experiments through robust, efficient comparison to public databases
transferlearning for small training set object detection
Working repository for Computer Vision course 2018.
Transfer Learning and Data Augmentation Techniques for Sketch Recognition
Android Application with Tensorflow Backend for Plant Image Classification
In Repository you can find various problem solved using Deep learning algorithm like Artificial Neural Network,Convolutional Neural network,Recurrent Neural Network, AutoEncoder with Keras
Fashion Image CNN Classifier using Keras
Implementation of various basic layers forward and back propagation. CS 231n Stanford Spring 2018: Convolutional Neural Networks for Visual Recognition. Solutions to Assignments
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.
Vancouver School of AI - Image Classification
Fork of initial project, in order to use Webcam and Machine Learning instead of keyboard to drive the car.
Pipeline to process real-world, user-supplied images. Given an image of a dog, the algorithm will identify an estimate of the canine’s breed.
Developing and comparing deep learning models for identifying Covid-19 diseases on CT and X-ray images.
Special Problem Project
This repository contains solving of NLP problems using transfer learning
Transfer Learning on my butterfly images using PyTorch
This endeavor of ours aims to leverage the potential of computer vision and deep learning to classify trees.
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