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 4601–4650 of 10307 papers

TitleStatusHype
KTN: Knowledge Transfer Network for Learning Multi-person 2D-3D CorrespondencesCode0
MEStereo-Du2CNN: A Novel Dual Channel CNN for Learning Robust Depth Estimates from Multi-exposure Stereo Images for HDR 3D Applications—0
Supervised learning of random quantum circuits via scalable neural networksCode0
Improving Localization for Semi-Supervised Object DetectionCode0
Remote Sensing Image Classification using Transfer Learning and Attention Based Deep Neural Network—0
Deep representation of EEG data from Spatio-Spectral Feature Images—0
A Neural Network Based Method with Transfer Learning for Genetic Data Analysis—0
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image ClassificationCode1
Technical Report: Combining knowledge from Transfer Learning during training and Wide ResnetsCode0
An Empirical Analysis on the Vulnerabilities of End-to-End Speech Segregation Models—0
Scalable Neural Data Server: A Data Recommender for Transfer Learning—0
Transfer Learning for Robust Low-Resource Children's Speech ASR with Transformers and Source-Filter Warping—0
Terrain Classification using Transfer Learning on Hyperspectral Images: A Comparative study—0
Learning Multi-Task Transferable Rewards via Variational Inverse Reinforcement Learning—0
Agricultural Plantation Classification using Transfer Learning Approach based on CNN—0
CLiMB: A Continual Learning Benchmark for Vision-and-Language TasksCode1
Motley: Benchmarking Heterogeneity and Personalization in Federated LearningCode0
Multistream Gaze Estimation with Anatomical Eye Region Isolation by Synthetic to Real Transfer LearningCode1
A Survey on Computational Intelligence-based Transfer Learning—0
Multi-Classification of Brain Tumor Images Using Transfer Learning Based Deep Neural Network—0
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image ClassificationCode1
COVID-19 Detection using Transfer Learning with Convolutional Neural Network—0
CtrlFormer: Learning Transferable State Representation for Visual Control via TransformerCode1
TLETA: Deep Transfer Learning and Integrated Cellular Knowledge for Estimated Time of Arrival Prediction—0
A Look at Value-Based Decision-Time vs. Background Planning Methods Across Different Settings—0
Assessing the Value of Transfer Learning Metrics for RF Domain Adaptation—0
Towards Diverse Evaluation of Class Incremental Learning: A Representation Learning Perspective—0
Recursive Neural Programs: Variational Learning of Image Grammars and Part-Whole Hierarchies—0
DRAFT: A Novel Framework to Reduce Domain Shifting in Self-supervised Learning and Its Application to Children's ASR—0
CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World DomainsCode1
Longitudinal detection of new MS lesions using Deep Learning—0
Multi scale Feature Extraction and Fusion for Online Knowledge Distillation—0
Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential RecommendationCode1
A Novel Implementation of Machine Learning for the Efficient, Explainable Diagnosis of COVID-19 from Chest CT—0
Hybrid thermal modeling of additive manufacturing processes using physics-informed neural networks for temperature prediction and parameter identificationCode1
Subsurface Depths Structure Maps Reconstruction with Generative Adversarial Networks—0
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification—0
Tackling Data Scarcity with Transfer Learning: A Case Study of Thickness Characterization from Optical Spectra of Perovskite Thin Films—0
FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks—0
FreeTransfer-X: Safe and Label-Free Cross-Lingual Transfer from Off-the-Shelf Models—0
Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning—0
Evaluating histopathology transfer learning with ChampKitCode1
Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition—0
Quantitative Imaging Principles Improves Medical Image LearningCode0
LST: Ladder Side-Tuning for Parameter and Memory Efficient Transfer LearningCode2
The Modality Focusing Hypothesis: Towards Understanding Crossmodal Knowledge DistillationCode1
TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback—0
Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets—0
DeepEmotex: Classifying Emotion in Text Messages using Deep Transfer Learning—0
PAC-Net: A Model Pruning Approach to Inductive Transfer Learning—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