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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 1151–1200 of 10307 papers

TitleStatusHype
CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World DomainsCode1
Can AI help in screening Viral and COVID-19 pneumonia?Code1
Detecting Omissions in Geographic Maps through Computer VisionCode1
Detection and Classification of Diabetic Retinopathy using Deep Learning Algorithms for Segmentation to Facilitate Referral Recommendation for Test and Treatment PredictionCode1
Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural NetworksCode1
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resourcesCode1
Differencing based Self-supervised pretraining for Scene Change DetectionCode1
Open-Pose 3D Zero-Shot Learning: Benchmark and ChallengesCode1
CALIP: Zero-Shot Enhancement of CLIP with Parameter-free AttentionCode1
Can LLMs' Tuning Methods Work in Medical Multimodal Domain?Code1
Byakto Speech: Real-time long speech synthesis with convolutional neural network: Transfer learning from English to BanglaCode1
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent AlignmentCode1
Disentangling Spatial and Temporal Learning for Efficient Image-to-Video Transfer LearningCode1
Distance-Based Regularisation of Deep Networks for Fine-TuningCode1
Distilling Knowledge from Graph Convolutional NetworksCode1
Distillation from Heterogeneous Models for Top-K RecommendationCode1
Neural Model Reprogramming with Similarity Based Mapping for Low-Resource Spoken Command RecognitionCode1
Distribution-aware Knowledge Prototyping for Non-exemplar Lifelong Person Re-identificationCode1
DOCKSTRING: easy molecular docking yields better benchmarks for ligand designCode1
ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft PromptsCode1
Uncovering the Connections Between Adversarial Transferability and Knowledge TransferabilityCode1
The Surprising Positive Knowledge Transfer in Continual 3D Object Shape ReconstructionCode1
Neural Architecture Search using Deep Neural Networks and Monte Carlo Tree SearchCode1
Attention-Based Deep Learning Framework for Human Activity Recognition with User AdaptationCode1
Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?Code1
Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across CitiesCode1
DeepGaze IIE: Calibrated prediction in and out-of-domain for state-of-the-art saliency modelingCode1
WONDERBREAD: A Benchmark for Evaluating Multimodal Foundation Models on Business Process Management TasksCode1
DREAM+: Efficient Dataset Distillation by Bidirectional Representative MatchingCode1
Drug and Disease Interpretation Learning with Biomedical Entity Representation TransformerCode1
DTL: Disentangled Transfer Learning for Visual RecognitionCode1
Duality Diagram Similarity: a generic framework for initialization selection in task transfer learningCode1
3D Point Cloud Registration with Multi-Scale Architecture and Unsupervised Transfer LearningCode1
Dynamic Domain Adaptation for Efficient InferenceCode1
A Study of Face Obfuscation in ImageNetCode1
AttentionHTR: Handwritten Text Recognition Based on Attention Encoder-Decoder NetworksCode1
EEG Channel Interpolation Using Deep Encoder-decoder NetwoksCode1
EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIsCode1
EEV: A Large-Scale Dataset for Studying Evoked Expressions from VideoCode1
Effect of Pre-Training Scale on Intra- and Inter-Domain Full and Few-Shot Transfer Learning for Natural and Medical X-Ray Chest ImagesCode1
A Chinese Corpus for Fine-grained Entity TypingCode1
Benchmarking and scaling of deep learning models for land cover image classificationCode1
Audio-based Near-Duplicate Video Retrieval with Audio Similarity LearningCode1
Efficient Fine-tuning of Audio Spectrogram Transformers via Soft Mixture of AdaptersCode1
Calibration-free online test-time adaptation for electroencephalography motor imagery decodingCode1
Efficient Training of Large Vision Models via Advanced Automated Progressive LearningCode1
Learning Efficient Vision Transformers via Fine-Grained Manifold DistillationCode1
Domain Consistency Representation Learning for Lifelong Person Re-IdentificationCode1
Classification of animal sounds in a hyperdiverse rainforest using Convolutional Neural NetworksCode1
Bridging the Source-to-target Gap for Cross-domain Person Re-Identification with Intermediate DomainsCode1
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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