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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4026–4050 of 10307 papers

TitleStatusHype
CLCE: An Approach to Refining Cross-Entropy and Contrastive Learning for Optimized Learning Fusion—0
A Privacy-Preserving Framework with Multi-Modal Data for Cross-Domain Recommendation—0
Few-shot Classification via Ensemble Learning with Multi-Order Statistics—0
FEW SHOT CROP MAPPING USING TRANSFORMERS AND TRANSFER LEARNING WITH SENTINEL-2 TIME SERIES: CASE OF KAIROUAN TUNISIA—0
Few-Shot Cross-Lingual TTS Using Transferable Phoneme Embedding—0
Adverse Drug Reaction Detection in Twitter Using RoBERTa and Rules—0
Few-Shot Dialogue Summarization via Skeleton-Assisted Prompt Transfer in Prompt Tuning—0
Few-Shot Domain Adaptation for Grammatical Error Correction via Meta-Learning—0
Few-shot fault diagnosis based on multi-scale graph convolution filtering for industry—0
Eva-KELLM: A New Benchmark for Evaluating Knowledge Editing of LLMs—0
Class Subset Selection for Transfer Learning using Submodularity—0
\'Etude de l'apprentissage par transfert de syst\`emes de traduction automatique neuronaux (Study on transfer learning in neural machine translation )—0
Class-Specific Data Augmentation: Bridging the Imbalance in Multiclass Breast Cancer Classification—0
A Privacy-Preserving Domain Adversarial Federated learning for multi-site brain functional connectivity analysis—0
Ethio-Fake: Cutting-Edge Approaches to Combat Fake News in Under-Resourced Languages Using Explainable AI—0
Few-Shot Learning-Based Human Activity Recognition—0
A Multi-stage Transfer Learning Framework for Diabetic Retinopathy Grading on Small Data—0
Class-Specific Channel Attention for Few-Shot Learning—0
Estimating the influence of auxiliary tasks for multi-task learning of sequence tagging tasks—0
Estimating State of Charge for xEV batteries using 1D Convolutional Neural Networks and Transfer Learning—0
When Few-Shot Learning Meets Video Object Detection—0
Class Similarity-Based Multimodal Classification under Heterogeneous Category Sets—0
Few-Shot Load Forecasting Under Data Scarcity in Smart Grids: A Meta-Learning Approach—0
A privacy-preserving data storage and service framework based on deep learning and blockchain for construction workers' wearable IoT sensors—0
Adversary ML Resilience in Autonomous Driving Through Human Centered Perception Mechanisms—0
Show:102550
← PrevPage 162 of 413Next →
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