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 7501–7550 of 10307 papers

TitleStatusHype
Adaptable image quality assessment using meta-reinforcement learning of task amenability—0
Adapt and Align to Improve Zero-Shot Sketch-Based Image Retrieval—0
Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification—0
Adaptation of Deep Bidirectional Transformers for Afrikaans Language—0
ADAPT : Awesome Domain Adaptation Python Toolbox—0
Adapted End-to-End Coreference Resolution System for Anaphoric Identities in Dialogues—0
Adapted tree boosting for Transfer Learning—0
Adapter Pruning using Tropical Characterization—0
Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification Tasks—0
Adapting BERT to Implicit Discourse Relation Classification with a Focus on Discourse Connectives—0
Adapting CRISP-DM for Idea Mining: A Data Mining Process for Generating Ideas Using a Textual Dataset—0
Adapting Models to Signal Degradation using Distillation—0
GLAM: Glomeruli Segmentation for Human Pathological Lesions using Adapted Mouse Model—0
Adapting Multilingual NMT to Extremely Low Resource Languages FBK’s Participation in the Basque-English Low-Resource MT Task, IWSLT 2018—0
Adapting Pre-trained Language Models for Quantum Natural Language Processing—0
Adapting Task-Oriented Dialogue Models for Email Conversations—0
Adapting TTS models For New Speakers using Transfer Learning—0
Adaptive Adversarial Network for Source-Free Domain Adaptation—0
Adaptive Aggregation for Safety-Critical Control—0
Adaptive Bi-Recommendation and Self-Improving Network for Heterogeneous Domain Adaptation-Assisted IoT Intrusion Detection—0
Adaptive Defective Area Identification in Material Surface Using Active Transfer Learning-based Level Set Estimation—0
Adaptive Explicit Knowledge Transfer for Knowledge Distillation—0
Adaptive Feature Ranking for Unsupervised Transfer Learning—0
Adaptive Image Restoration for Video Surveillance: A Real-Time Approach—0
Adaptive Invariance for Molecule Property Prediction—0
Adaptive Label Noise Cleaning With Meta-Supervision for Deep Face Recognition—0
Adaptive Label Smoothing—0
Adaptive Learning of Design Strategies over Non-Hierarchical Multi-Fidelity Models via Policy Alignment—0
Adaptive Learning to Speed-Up Control of Prosthetic Hands: a Few Things Everybody Should Know—0
Adaptively-Accumulated Knowledge Transfer for Partial Domain Adaptation—0
Adaptive multi-channel event segmentation and feature extraction for monitoring health outcomes—0
Adaptive Multi-Fidelity Reinforcement Learning for Variance Reduction in Engineering Design Optimization—0
Adaptive Multiscale Retinal Diagnosis: A Hybrid Trio-Model Approach for Comprehensive Fundus Multi-Disease Detection Leveraging Transfer Learning and Siamese Networks—0
Adaptive Multi-Source Causal Inference—0
Adaptive Part Learning for Fine-Grained Generalized Category Discovery: A Plug-and-Play Enhancement—0
Adaptive Physics-informed Neural Networks: A Survey—0
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows—0
Adaptive Prototype Knowledge Transfer for Federated Learning with Mixed Modalities and Heterogeneous Tasks—0
Adaptive ship-radiated noise recognition with learnable fine-grained wavelet transform—0
Adaptive Sparse Transformer for Multilingual Translation—0
Adaptive Target Localization under Uncertainty using Multi-Agent Deep Reinforcement Learning with Knowledge Transfer—0
Adaptive Trajectory Prediction via Transferable GNN—0
Adaptive transfer learning—0
Adaptive Transfer Learning: a simple but effective transfer learning—0
Adaptive Transfer Learning for Multi-Label Emotion Classification—0
Adaptive Transfer Learning for Plant Phenotyping—0
Adaptive Transfer Learning in Deep Neural Networks: Wind Power Prediction using Knowledge Transfer from Region to Region and Between Different Task Domains—0
Adaptive Transfer Learning of Multi-View Time Series Classification—0
Adaptive Variance Thresholding: A Novel Approach to Improve Existing Deep Transfer Vision Models and Advance Automatic Knee-Joint Osteoarthritis Classification—0
Adaptive Variants of Optimal Feedback Policies—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