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 9401–9450 of 10307 papers

TitleStatusHype
Transfer Learning and Organic Computing for Autonomous Vehicles—0
Ensemble of Convolutional Neural Networks for Dermoscopic Images Classification—0
Building medical image classifiers with very limited data using segmentation networks—0
Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation—0
Intracerebral EEG Artifact Identification Using Convolutional Neural NetworksCode0
A Transfer Learning based Feature-Weak-Relevant Method for Image Clustering—0
Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks—0
Addressee and Response Selection for Multilingual ConversationCode0
Unsupervised Learning of Sentence Representations Using Sequence Consistency—0
Transfer Learning Enhanced Common Spatial Pattern Filtering for Brain Computer Interfaces (BCIs): Overview and a New Approach—0
An Occam's Razor View on Learning Audiovisual Emotion Recognition with Small Training Sets—0
Multi-Label Zero-Shot Learning with Transfer-Aware Label Embedding Projection—0
DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer TranscriptomeCode0
Detection and Segmentation of Manufacturing Defects with Convolutional Neural Networks and Transfer Learning—0
Deep Transfer Learning for EEG-based Brain Computer Interface—0
A Survey on Deep Transfer Learning—0
Autoencoder Based Sample Selection for Self-Taught Learning—0
Smart City Development with Urban Transfer Learning—0
Language Model Supervision for Handwriting Recognition Model Adaptation—0
Knowledge as A Bridge: Improving Cross-domain Answer Selection with External Knowledge—0
Adaptive Multi-Task Transfer Learning for Chinese Word Segmentation in Medical TextCode0
Learning Multilingual Topics from Incomparable Corpora—0
Convolutional Neural Network for Universal Sentence Embeddings—0
Learning to Progressively Recognize New Named Entities with Sequence to Sequence Models—0
Multi-task and Multi-lingual Joint Learning of Neural Lexical Utterance Classification based on Partially-shared Modeling—0
Farewell Freebase: Migrating the SimpleQuestions Dataset to DBpediaCode0
Using Neural Transfer Learning for Morpho-syntactic Tagging of South-Slavic Languages Tweets—0
Transfer Learning for Entity Recognition of Novel ClassesCode0
TRAC-1 Shared Task on Aggression Identification: IIT(ISM)@COLING'18—0
Transferred Embeddings for Igbo Similarity, Analogy, and Diacritic Restoration Tasks—0
Transfer Learning for a Letter-Ngrams to Word Decoder in the Context of Historical Handwriting Recognition with Scarce Resources—0
Brain MRI Image Super Resolution using Phase Stretch Transform and Transfer LearningCode0
Deep Cross Modal Learning for Caricature Verification and Identification(CaVINet)Code0
Improving Transferability of Deep Neural Networks—0
Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning—0
Semi-supervised Transfer Learning for Image Rain RemovalCode0
Visual Analogies between Atari Games for Studying Transfer Learning in RL—0
Do Better ImageNet Models Transfer Better... for Image Recommendation?—0
Attend Before you Act: Leveraging human visual attention for continual learningCode0
CReaM: Condensed Real-time Models for Depth Prediction using Convolutional Neural Networks—0
Knowledge-based Transfer Learning ExplanationCode0
Asynchronous Advantage Actor-Critic Agent for Starcraft II—0
Surgical Phase Recognition of Short Video Shots Based on Temporal Modeling of Deep Features—0
Deep Transfer Learning for Cross-domain Activity Recognition—0
Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding—0
Bio-Measurements Estimation and Support in Knee Recovery through Machine Learning—0
Transfer Learning for Action Unit Recognition—0
Visual Domain Adaptation with Manifold Embedded Distribution Alignment—0
Metric Embedding Autoencoders for Unsupervised Cross-Dataset Transfer Learning—0
CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement—0
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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