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 3001–3050 of 10307 papers

TitleStatusHype
Dimensionality Expansion of Load Monitoring Time Series and Transfer Learning for EMS—0
Binary Paragraph Vectors—0
Analysis of the Two-Step Heterogeneous Transfer Learning for Laryngeal Blood Vessel Classification: Issue and Improvement—0
A Data-Driven Evolutionary Transfer Optimization for Expensive Problems in Dynamic Environments—0
An Evaluation of Progressive Neural Networksfor Transfer Learning in Natural Language Processing—0
Direct Network Transfer: Transfer Learning of Sentence Embeddings for Semantic Similarity—0
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG—0
BioAMA: Towards an End to End BioMedical Question Answering System—0
Discovering Hidden Physics Behind Transport Dynamics—0
BioBERTpt - A Portuguese Neural Language Model for Clinical Named Entity Recognition—0
Effective Analog ICs Floorplanning with Relational Graph Neural Networks and Reinforcement Learning—0
Deep-Learning Driven Noise Reduction for Reduced Flux Computed Tomography—0
Biologically inspired sleep algorithm for artificial neural networks—0
BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network—0
``Deep'' Learning : Detecting Metaphoricity in Adjective-Noun Pairs—0
Discriminative Label Consistent Domain Adaptation—0
Discriminative Partial Domain Adversarial Network—0
Discriminative Pattern Calibration Mechanism for Source-Free Domain Adaptation—0
Autonomous learning of multiple, context-dependent tasks—0
Discriminative Transfer Learning with Tree-based Priors—0
Deep-Learning Convolutional Neural Networks for scattered shrub detection with Google Earth Imagery—0
Disease Classification and Impact of Pretrained Deep Convolution Neural Networks on Diverse Medical Imaging Datasets across Imaging Modalities—0
Autonomous Extraction of a Hierarchical Structure of Tasks in Reinforcement Learning, A Sequential Associate Rule Mining Approach—0
Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation—0
Disengagement Cause-and-Effect Relationships Extraction Using an NLP Pipeline—0
Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction—0
A Data-Driven Approach to Improve 3D Head-Pose Estimation—0
Disentangled Adversarial Transfer Learning for Physiological Biosignals—0
EEG-based Cognitive Load Classification using Feature Masked Autoencoding and Emotion Transfer Learning—0
Deep learning-based Visual Measurement Extraction within an Adaptive Digital Twin Framework from Limited Data Using Transfer Learning—0
Deep learning-based variational autoencoder for classification of quantum and classical states of light—0
Disentangled State Space Representations—0
Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning—0
BIRD: Behavior Induction via Representation-structure Distillation—0
Autonomous crater detection on asteroids using a fully-convolutional neural network—0
Disentangling Quantum and Classical Contributions in Hybrid Quantum Machine Learning Architectures—0
Disentangling Space and Time in Video with Hierarchical Variational Auto-encoders—0
Deep Learning-Based Transfer Learning for Classification of Cassava Disease—0
AutoML Systems For Medical Imaging—0
A Data Driven Approach for Compound Figure Separation Using Convolutional Neural Networks—0
EEG-Based Mental Imagery Task Adaptation via Ensemble of Weight-Decomposed Low-Rank Adapters—0
Disjoint Label Space Transfer Learning with Common Factorised Space—0
Deep Learning-based Prediction of Stress and Strain Maps in Arterial Walls for Improved Cardiovascular Risk Assessment—0
Deep learning based prediction of Alzheimer's disease from magnetic resonance images—0
Analysis of Multilingual Sequence-to-Sequence speech recognition systems—0
Distant Transfer Learning via Deep Random Walk—0
Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning—0
Deep-Learning-Based Markerless Pose Estimation Systems in Gait Analysis: DeepLabCut Custom Training and the Refinement Function—0
An Analysis of Semantically-Aligned Speech-Text Embeddings—0
EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications—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