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 7201–7225 of 10307 papers

TitleStatusHype
Light3DPose: Real-time Multi-Person 3D PoseEstimation from Multiple Views—0
TgDLF2.0: Theory-guided deep-learning for electrical load forecasting via Transformer and transfer learning—0
A neural network to classify metaphorical violence on cable news—0
SkeleTR: Towards Skeleton-based Action Recognition in the Wild—0
SkeleTR: Towrads Skeleton-based Action Recognition in the Wild—0
Sketch-a-Classifier: Sketch-based Photo Classifier Generation—0
Lightweight Convolutional Neural Networks for Retinal Disease Classification—0
Skilful Precipitation Nowcasting Using NowcastNet—0
Lightweight Encoder-Decoder Architecture for Foot Ulcer Segmentation—0
Light-weight Head Pose Invariant Gaze Tracking—0
A Neural Network Model for Part-Of-Speech Tagging of Social Media Texts—0
A Neural Network Based Method with Transfer Learning for Genetic Data Analysis—0
Limitations of Knowledge Distillation for Zero-shot Transfer Learning—0
Skill Transfer in Deep Reinforcement Learning under Morphological Heterogeneity—0
Limits of Model Selection under Transfer Learning—0
Limits of Transfer Learning—0
An Euler-based GAN for time series—0
Skin Cancer Classification using Inception Network and Transfer Learning—0
Linguist Geeks on WNUT-2020 Task 2: COVID-19 Informative Tweet Identification using Progressive Trained Language Models and Data Augmentation—0
Linguistic approach based Transfer Learning for Sentiment Classification in Hindi—0
Linguistic Considerations in Automatic Question Generation—0
Discovering Salient Neurons in Deep NLP Models—0
Linguistic Knowledge Transfer Learning for Speech Enhancement—0
Linked Adapters: Linking Past and Future to Present for Effective Continual Learning—0
An Empirical Study on Data Leakage and Generalizability of Link Prediction Models for Issues and Commits—0
Show:102550
← PrevPage 289 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