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 8401–8450 of 10307 papers

TitleStatusHype
Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning—0
Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies—0
Boosting multi-demographic federated learning for chest x-ray analysis using general-purpose self-supervised representations—0
Boosting offline handwritten text recognition in historical documents with few labeled lines—0
Boosting pathology detection in infants by deep transfer learning from adult speech—0
Boosting Personalised Musculoskeletal Modelling with Physics-informed Knowledge Transfer—0
Boosting Self-Supervised Learning via Knowledge Transfer—0
Boosting Single-Frame 3D Object Detection by Simulating Multi-Frame Point Clouds—0
Boosting Template-based SSVEP Decoding by Cross-domain Transfer Learning—0
Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data—0
Boosting Transformers for Job Expression Extraction and Classification in a Low-Resource Setting—0
Bootstrap an end-to-end ASR system by multilingual training, transfer learning, text-to-text mapping and synthetic audio—0
Towards Complementary Knowledge Distillation for Efficient Dense Image Prediction—0
Bounds on the Minimax Rate for Estimating a Prior over a VC Class from Independent Learning Tasks—0
Brain2Model Transfer: Training sensory and decision models with human neural activity as a teacher—0
Brain informed transfer learning for categorizing construction hazards—0
Brain-mediated Transfer Learning of Convolutional Neural Networks—0
Brain MRI detection by Sematic Segmentation models- Transfer Learning approach—0
BrainTalker: Low-Resource Brain-to-Speech Synthesis with Transfer Learning using Wav2Vec 2.0—0
Brain Tumor Classification on MRI in Light of Molecular Markers—0
Brain Tumor Detection Using Deep Learning Approaches—0
A Machine Learning-Based Framework for Assessing Cryptographic Indistinguishability of Lightweight Block Ciphers—0
BreakingNews: Article Annotation by Image and Text Processing—0
Breaking the Architecture Barrier: A Method for Efficient Knowledge Transfer Across Networks—0
Breast Cancer Diagnosis with Transfer Learning and Global Pooling—0
Breast Cancer Image Classification Method Based on Deep Transfer Learning—0
Breast Lump Detection and Localization with a Tactile Glove Using Deep Learning—0
Breast mass detection in digital mammography based on anchor-free architecture—0
Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfer—0
BridgeNets: Student-Teacher Transfer Learning Based on Recursive Neural Networks and its Application to Distant Speech Recognition—0
Bridge the Gap Between Visual and Linguistic Comprehension for Generalized Zero-shot Semantic Segmentation—0
Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation—0
Bridging Domain Gap for Flight-Ready Spaceborne Vision—0
Bridging Ears and Eyes: Analyzing Audio and Visual Large Language Models to Humans in Visible Sound Recognition and Reducing Their Sensory Gap via Cross-Modal Distillation—0
Bridging Industrial Expertise and XR with LLM-Powered Conversational Agents—0
Bridging Modalities: Enhancing Cross-Modality Hate Speech Detection with Few-Shot In-Context Learning—0
Bridging the Bosphorus: Advancing Turkish Large Language Models through Strategies for Low-Resource Language Adaptation and Benchmarking—0
Bridging the Gap: Transfer Learning from English PLMs to Malaysian English—0
Bridging The Multi-Modality Gaps of Audio, Visual and Linguistic for Speech Enhancement—0
Bristle: Decentralized Federated Learning in Byzantine, Non-i.i.d. Environments—0
BugWhisperer: Fine-Tuning LLMs for SoC Hardware Vulnerability Detection—0
Multihop: Leveraging Complex Models to Learn Accurate Simple Models—0
Building Advanced Dialogue Managers for Goal-Oriented Dialogue Systems—0
Building and Road Segmentation Using EffUNet and Transfer Learning Approach—0
Building a Question and Answer System for News Domain—0
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach—0
Building Efficient Lightweight CNN Models—0
Building Height Prediction with Instance Segmentation—0
Building Inspection Toolkit: Unified Evaluation and Strong Baselines for Damage Recognition—0
Building medical image classifiers with very limited data using segmentation networks—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