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 9351–9400 of 10307 papers

TitleStatusHype
Contour Knowledge Transfer for Salient Object DetectionCode1
A New Large Scale Dynamic Texture Dataset with Application to ConvNet Understanding—0
Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation—0
Gromov-Wasserstein Alignment of Word Embedding Spaces—0
AISHELL-2: Transforming Mandarin ASR Research Into Industrial Scale—0
Automatic Lung Cancer Prediction from Chest X-ray Images Using Deep Learning Approach—0
DADA: Deep Adversarial Data Augmentation for Extremely Low Data Regime ClassificationCode0
The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments—0
Efficient keyword spotting using time delay neural networks—0
Adapting Word Embeddings to New Languages with Morphological and Phonological Subword RepresentationsCode0
Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks—0
Zero-shot Transfer Learning for Semantic Parsing—0
Sentence Embeddings in NLI with Iterative Refinement EncodersCode0
Amobee at IEST 2018: Transfer Learning from Language Models—0
Meta-Learning for Low-Resource Neural Machine Translation—0
Financial Aspect-Based Sentiment Analysis using Deep Representations—0
Transfer Learning for Estimating Causal Effects using Neural Networks—0
Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition—0
Multidomain Document Layout Understanding using Few Shot Object Detection—0
Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning—0
Lessons from Natural Language Inference in the Clinical DomainCode0
DeeSIL: Deep-Shallow Incremental Learning—0
XL-NBT: A Cross-lingual Neural Belief Tracking FrameworkCode0
CellLineNet: End-to-End Learning and Transfer Learning For Multiclass Epithelial Breast cell Line Classification via a Convolutional Neural Network—0
Collaborative Pressure Ulcer Prevention: An Automated Skin Damage and Pressure Ulcer Assessment Tool for Nursing Professionals, Patients, Family Members and Carers—0
Transfer Learning and Organic Computing for Autonomous Vehicles—0
Building medical image classifiers with very limited data using segmentation networks—0
Ensemble of Convolutional Neural Networks for Dermoscopic Images Classification—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
Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment ApproachCode1
An Occam's Razor View on Learning Audiovisual Emotion Recognition with Small Training Sets—0
Detection and Segmentation of Manufacturing Defects with Convolutional Neural Networks and Transfer Learning—0
DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer TranscriptomeCode0
Multi-Label Zero-Shot Learning with Transfer-Aware Label Embedding Projection—0
Deep Transfer Learning for EEG-based Brain Computer Interface—0
A Survey on Deep Transfer Learning—0
Smart City Development with Urban Transfer Learning—0
Autoencoder Based Sample Selection for Self-Taught Learning—0
Language Model Supervision for Handwriting Recognition Model Adaptation—0
Adaptive Multi-Task Transfer Learning for Chinese Word Segmentation in Medical TextCode0
Learning Multilingual Topics from Incomparable Corpora—0
Multi-task and Multi-lingual Joint Learning of Neural Lexical Utterance Classification based on Partially-shared Modeling—0
Learning to Progressively Recognize New Named Entities with Sequence to Sequence Models—0
Knowledge as A Bridge: Improving Cross-domain Answer Selection with External Knowledge—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