SOTAVerified

Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

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Showing 9001–9050 of 10307 papers

TitleStatusHype
Colorectal cancer diagnosis from histology images: A comparative study—0
A Seed-Augment-Train Framework for Universal Digit Classification—0
A novel machine learning based framework for detection of Autism Spectrum Disorder (ASD)—0
Understanding Unconventional Preprocessors in Deep Convolutional Neural Networks for Face Identification—0
Weighted Multisource Tradaboost—0
On evaluating CNN representations for low resource medical image classification—0
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree SearchCode0
Domain Independent SVM for Transfer Learning in Brain Decoding—0
RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems—0
Training Data Independent Image Registration With GANs Using Transfer Learning And Segmentation Information—0
Apple Leaf Disease Identification through Region-of-Interest-Aware Deep Convolutional Neural Network—0
Manifold Criterion Guided Transfer Learning via Intermediate Domain GenerationCode0
Few-Shot Learning-Based Human Activity Recognition—0
Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning—0
Enhanced Transfer Learning with ImageNet Trained Classification Layer—0
Automatic Labeling of Data for Transfer Learning—0
Learning To Avoid Negative Transfer in Few Shot Transfer Learning—0
Automated Classification of Histopathology Images Using Transfer LearningCode0
What Synthesis is Missing: Depth Adaptation Integrated with Weak Supervision for Indoor Scene Parsing—0
A Machine Learning approach to Risk Minimisation in Electricity Markets with Coregionalized Sparse Gaussian Processes—0
Overcoming Small Minirhizotron Datasets Using Transfer LearningCode0
PPGnet: Deep Network for Device Independent Heart Rate Estimation from Photoplethysmogram—0
Deep Radiomics for Brain Tumor Detection and Classification from Multi-Sequence MRI—0
Cross Domain Knowledge Transfer for Unsupervised Vehicle Re-identification—0
Domain adaptation for holistic skin detection—0
Task Decomposition for Iterative Learning Model Predictive Control—0
Improving Prostate Cancer Detection with Breast Histopathology Images—0
To Tune or Not to Tune? Adapting Pretrained Representations to Diverse Tasks—0
Cleaning tasks knowledge transfer between heterogeneous robots: a deep learning approach—0
Paradox in Deep Neural Networks: Similar yet Different while Different yet Similar—0
Dense Classification and Implanting for Few-Shot Learning—0
Practical Semantic Parsing for Spoken Language Understanding—0
Named Entity Recognition for Electronic Health Records: A Comparison of Rule-based and Machine Learning Approaches—0
Mutual Clustering on Comparative Texts via Heterogeneous Information Networks—0
Everything old is new again: A multi-view learning approach to learning using privileged information and distillation—0
Learning Hierarchical Teaching Policies for Cooperative Agents—0
Machine learning method for single trajectory characterizationCode0
Ultrasound Image Representation Learning by Modeling Sonographer Visual Attention—0
Transfer Learning Using Ensemble Neural Networks for Organic Solar Cell ScreeningCode0
ViTOR: Learning to Rank Webpages Based on Visual Features—0
Learning from Higher-Layer Feature Visualizations—0
Deep Transfer Learning for Multiple Class Novelty DetectionCode0
PROPS: Probabilistic personalization of black-box sequence modelsCode0
Defining Image Memorability using the Visual Memory Schema—0
Zero-Shot Task TransferCode0
Detecting dementia in Mandarin Chinese using transfer learning from a parallel corpus—0
neuralRank: Searching and ranking ANN-based model repositories—0
Efficient Reinforcement Learning for StarCraft by Abstract Forward Models and Transfer LearningCode0
Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis—0
Optimal Projection Guided Transfer Hashing for Image RetrievalCode0
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All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified