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 5351–5400 of 10307 papers

TitleStatusHype
AdaptCL: Adaptive Continual Learning for Tackling Heterogeneity in Sequential DatasetsCode0
Multi-Level Fine-Tuning, Data Augmentation, and Few-Shot Learning for Specialized Cyber Threat Intelligence—0
A Transferable Recommender Approach for Selecting the Best Density Functional Approximations in Chemical Discovery—0
Deep transfer learning method based on automatic domain alignment and moment matchingCode0
Sequence Models for Drone vs Bird Classification—0
Completing Single-Cell DNA Methylome Profiles via Transfer Learning Together With KL-DivergenceCode0
Federated Semi-Supervised Domain Adaptation via Knowledge Transfer—0
A Novel Neural Network Training Method for Autonomous Driving Using Semi-Pseudo-Labels and 3D Data Augmentations—0
What Do We Maximize in Self-Supervised Learning?—0
Similarity of Pre-trained and Fine-tuned Representations—0
On the cross-lingual transferability of multilingual prototypical models across NLU tasks—0
Multilingual Transformer Encoders: a Word-Level Task-Agnostic EvaluationCode0
Self-Supervised Interactive Object Segmentation Through a Singulation-and-Grasping Approach—0
On the Usability of Transformers-based models for a French Question-Answering task—0
Revealing Secrets From Pre-trained Models—0
Assaying Out-Of-Distribution Generalization in Transfer LearningCode0
Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya-Watson RegressionCode0
Multimodal hierarchical Variational AutoEncoders with Factor Analysis latent spaceCode0
CTL-MTNet: A Novel CapsNet and Transfer Learning-Based Mixed Task Net for the Single-Corpus and Cross-Corpus Speech Emotion RecognitionCode0
Supervised Contrastive ResNet and Transfer Learning for the In-vehicle Intrusion Detection System—0
Coupling Adversarial Learning with Selective Voting Strategy for Distribution Alignment in Partial Domain Adaptation—0
An EfficientNet-based modified sigmoid transform for enhancing dermatological macro-images of melanoma and nevi skin lesionsCode0
Multi-Task and Transfer Learning for Federated Learning Applications—0
TSPipe: Learn from Teacher Faster with PipelinesCode0
DEXTER: An end-to-end system to extract table contents from electronic medical health documents—0
A Deep Learning-Based GPR Forward Solver for Predicting B-Scans of Subsurface Objects—0
A Transfer Learning Based Model for Text Readability Assessment in German—0
Continual Meta-Reinforcement Learning for UAV-Aided Vehicular Wireless Networks—0
On the Generalization for Transfer Learning: An Information-Theoretic Analysis—0
RE-Tagger: A light-weight Real-Estate Image Classifier—0
Transferability-Guided Cross-Domain Cross-Task Transfer Learning—0
An Interpretable Joint Nonnegative Matrix Factorization-Based Point Cloud Distance Measure—0
Multi-level Fusion of Wav2vec 2.0 and BERT for Multimodal Emotion RecognitionCode0
Real-Time And Robust 3D Object Detection with Roadside LiDARs—0
Dual-Correction Adaptation Network for Noisy Knowledge Transfer—0
Beyond Transfer Learning: Co-finetuning for Action Localisation—0
On Improving the Performance of Glitch Classification for Gravitational Wave Detection by using Generative Adversarial Networks—0
The Power of Transfer Learning in Agricultural Applications: AgriNet—0
G2L: A Geometric Approach for Generating Pseudo-labels that Improve Transfer Learning—0
Self-Supervised RF Signal Representation Learning for NextG Signal Classification with Deep Learning—0
Deep learning based Hand gesture recognition system and design of a Human-Machine Interface—0
An Embedding-Dynamic Approach to Self-supervised Learning—0
Distillation to Enhance the Portability of Risk Models Across Institutions with Large Patient Claims Database—0
Lightweight Encoder-Decoder Architecture for Foot Ulcer Segmentation—0
Low-resource Low-footprint Wake-word Detection using Knowledge Distillation—0
Pre-training Transformers for Molecular Property Prediction Using Reaction Prediction—0
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms—0
Test-time Adaptation for Real Image Denoising via Meta-transfer Learning—0
A Unified Meta-Learning Framework for Dynamic Transfer LearningCode0
Vision-and-Language PretrainingCode0
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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