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 8151–8200 of 10307 papers

TitleStatusHype
A Transfer Learning Method for Speech Emotion Recognition from Automatic Speech Recognition—0
A Transfer Learning Pipeline for Educational Resource Discovery with Application in Leading Paragraph Generation—0
A Transition-based System for Universal Dependency Parsing—0
Attentional Push: A Deep Convolutional Network for Augmenting Image Salience With Shared Attention Modeling in Social Scenes—0
Attention-Aware Generative Adversarial Networks (ATA-GANs)—0
Attention-based Domain Adaption Using Transfer Learning for Part-of-Speech Tagging: An Experiment on the Hindi language—0
Attention-based Modeling for Emotion Detection and Classification in Textual Conversations—0
Attention-based Multi-scale Gated Recurrent Encoder with Novel Correlation Loss for COVID-19 Progression Prediction—0
Attention-based Transfer Learning for Brain-computer Interface—0
Attention-based Wav2Text with Feature Transfer Learning—0
Attention Bridging Network for Knowledge Transfer—0
Attention-Gated Graph Convolutions for Extracting Drug Interaction Information from Drug Labels—0
Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline with Structural MRI—0
Attention-Guided Erasing: A Novel Augmentation Method for Enhancing Downstream Breast Density Classification—0
Attention Is All You Need For Blind Room Volume Estimation—0
Attention Is All You Need For Mixture-of-Depths Routing—0
Attention is All You Need to Optimize Wind Farm Operations and Maintenance—0
Attention module improves both performance and interpretability of 4D fMRI decoding neural network—0
Attention Option-Critic—0
An Attention Mechanism with Multiple Knowledge Sources for COVID-19 Detection from CT Images—0
Attentive Task-Agnostic Meta-Learning for Few-Shot Text Classification—0
Attr2Style: A Transfer Learning Approach for Inferring Fashion Styles via Apparel Attributes—0
Attractor learning for spatiotemporally chaotic dynamical systems using echo state networks with transfer learning—0
Attribute-Induced Bias Eliminating for Transductive Zero-Shot Learning—0
A Two stage Adaptive Knowledge Transfer Evolutionary Multi-tasking Based on Population Distribution for Multi/Many-Objective Optimization—0
A Two-stage Approach for Extending Event Detection to New Types via Neural Networks—0
A Two-Stage Approach towards Generalization in Knowledge Base Question Answering—0
A Two-Stage Approach towards Generalization in Knowledge Base Question Answering—0
Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing—0
Audio-visual scene classification: analysis of DCASE 2021 Challenge submissions—0
Audio-Visual Scene Classification Using A Transfer Learning Based Joint Optimization Strategy—0
Audiovisual transfer learning for audio tagging and sound event detection—0
Augment Before Copy-Paste: Data and Memory Efficiency-Oriented Instance Segmentation Framework for Sport-scenes—0
Augmenting Character Designers Creativity Using Generative Adversarial Networks—0
Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP—0
Augmenting Knowledge Distillation With Peer-To-Peer Mutual Learning For Model Compression—0
Augmenting Offline RL with Unlabeled Data—0
Augmenting Transfer Learning with Semantic Reasoning—0
Augmenting transferred representations for stock classification—0
AUKT: Adaptive Uncertainty-Guided Knowledge Transfer with Conformal Prediction—0
A Unified Deep Learning Approach for Prediction of Parkinson's Disease—0
A Unified Deep Transfer Learning Model for Accurate IoT Localization in Diverse Environments—0
A Unified Framework for Cross-Domain Recommendation—0
A Unified Framework for Heterogeneous Semi-supervised Learning—0
A Conceptual Framework for Lifelong Learning—0
A Unified View of Abstract Visual Reasoning Problems—0
A Universal Parent Model for Low-Resource Neural Machine Translation Transfer—0
Authorship Attribution in Bangla Literature (AABL) via Transfer Learning using ULMFiT—0
Autism Disease Detection Using Transfer Learning Techniques: Performance Comparison Between Central Processing Unit vs Graphics Processing Unit Functions for Neural Networks—0
Autism Spectrum Disorder Classification in Children based on Structural MRI Features Extracted using Contrastive Variational Autoencoder—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