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 7226–7250 of 10307 papers

TitleStatusHype
C2KD: Bridging the Modality Gap for Cross-Modal Knowledge Distillation—0
Teamwork Dimensions Classification Using BERT—0
Technical Language Supervision for Intelligent Fault Diagnosis in Process Industry—0
CACTUS: An Open Dataset and Framework for Automated Cardiac Assessment and Classification of Ultrasound Images Using Deep Transfer Learning—0
CactusNets: Layer Applicability as a Metric for Transfer Learning—0
TECM: Transfer Learning-based Evidential C-Means Clustering—0
TED-CDB: A Large-Scale Chinese Discourse Relation Dataset on TED Talks—0
Tel(s)-Telle(s)-Signs: Highly Accurate Automatic Crosslingual Hypernym Discovery—0
Temperate Fish Detection and Classification: a Deep Learning based Approach—0
Template Adaptation for Face Verification and Identification—0
Template-based Approach to Zero-shot Intent Recognition—0
Temporal Hockey Action Recognition via Pose and Optical Flows—0
Temporal Order Preserved Optimal Transport-based Cross-modal Knowledge Transfer Learning for ASR—0
Temporal Probabilistic Asymmetric Multi-task Learning—0
Adaptive Explicit Knowledge Transfer for Knowledge Distillation—0
Ten Challenging Problems in Federated Foundation Models—0
Adaptive Feature Ranking for Unsupervised Transfer Learning—0
Tensor Representation and Manifold Learning Methods for Remote Sensing Images—0
TenTrans Multilingual Low-Resource Translation System for WMT21 Indo-European Languages Task—0
Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney—0
Terahertz Pulse Shaping Using Diffractive Surfaces—0
CAE-DFKD: Bridging the Transferability Gap in Data-Free Knowledge Distillation—0
Terrain Classification using Transfer Learning on Hyperspectral Images: A Comparative study—0
CAKD: A Correlation-Aware Knowledge Distillation Framework Based on Decoupling Kullback-Leibler Divergence—0
Testing the Generalization Power of Neural Network Models Across NLI Benchmarks—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