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 71–80 of 10307 papers

TitleStatusHype
HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient TuningCode2
AXIAL: Attention-based eXplainability for Interpretable Alzheimer's Localized Diagnosis using 2D CNNs on 3D MRI brain scansCode2
T-FREE: Subword Tokenizer-Free Generative LLMs via Sparse Representations for Memory-Efficient EmbeddingsCode2
Automated MRI Quality Assessment of Brain T1-weighted MRI in Clinical Data Warehouses: A Transfer Learning Approach Relying on Artefact SimulationCode2
Large Scale Transfer Learning for Tabular Data via Language ModelingCode2
Enhancing Zero-Shot Facial Expression Recognition by LLM Knowledge TransferCode2
XTrack: Multimodal Training Boosts RGB-X Video Object TrackersCode2
FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic PredictionCode2
MRSegmentator: Multi-Modality Segmentation of 40 Classes in MRI and CTCode2
Efficient Remote Sensing with Harmonized Transfer Learning and Modality AlignmentCode2
Show:102550
← PrevPage 8 of 1031Next →
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