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 2601–2650 of 10307 papers

TitleStatusHype
Micrometer: Micromechanics Transformer for Predicting Mechanical Responses of Heterogeneous Materials—0
SeqNet: Sequential Networks for One-Shot Traffic Sign Recognition With Transfer LearningCode0
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks—0
Multiple-Exit Tuning: Towards Inference-Efficient Adaptation for Vision Transformer—0
Generalization in birdsong classification: impact of transfer learning methods and dataset characteristics—0
Transfer Learning and Double U-Net Empowered Wave Propagation Model in Complex Indoor Environment—0
Transfer Learning for E-commerce Query Product Type Prediction—0
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models—0
Transfer Learning with Clinical Concept Embeddings from Large Language Models—0
Context-Aware Predictive Coding: A Representation Learning Framework for WiFi SensingCode0
Exploring bat song syllable representations in self-supervised audio encoders—0
Deep Transfer Hashing for Adaptive Learning on Federated Streaming Data—0
Recognition of Harmful Phytoplankton from Microscopic Images using Deep Learning—0
Investigation on domain adaptation of additive manufacturing monitoring systems to enhance digital twin reusability—0
Rapid aerodynamic prediction of swept wings via physics-embedded transfer learning—0
E-Sort: Empowering End-to-end Neural Network for Multi-channel Spike Sorting with Transfer Learning and Fast Post-processingCode0
Efficient Low-Resolution Face Recognition via Bridge Distillation—0
Bridging Domain Gap for Flight-Ready Spaceborne Vision—0
Location based Probabilistic Load Forecasting of EV Charging Sites: Deep Transfer Learning with Multi-Quantile Temporal Convolutional Network—0
Using Large Language Models to Generate Clinical Trial Tables and Figures—0
Unleashing the Potential of Mamba: Boosting a LiDAR 3D Sparse Detector by Using Cross-Model Knowledge Distillation—0
Leveraging Distillation Techniques for Document Understanding: A Case Study with FLAN-T5—0
Analysis of Convolutional Neural Network-based Image Classifications: A Multi-Featured Application for Rice Leaf Disease Prediction and Recommendations for Farmers—0
RF-GML: Reference-Free Generative Machine Listener—0
A Comparative Study of Open Source Computer Vision Models for Application on Small Data: The Case of CFRP Tape Laying—0
Context-Aware Predictive Coding: A Representation Learning Framework for WiFi SensingCode0
On the Generalizability of Foundation Models for Crop Type MappingCode0
Comparative Analysis of Pretrained Audio Representations in Music Recommender SystemsCode0
Train-On-Request: An On-Device Continual Learning Workflow for Adaptive Real-World Brain Machine InterfacesCode0
DELTA: Dual Consistency Delving with Topological Uncertainty for Active Graph Domain AdaptationCode0
Using The Concept Hierarchy for Household Action Recognition—0
Exploring the Impact of Data Quantity on ASR in Extremely Low-resource Languages—0
TheraGen: Therapy for Every Generation—0
Learn from Balance: Rectifying Knowledge Transfer for Long-Tailed Scenarios—0
Transfer Learning Applied to Computer Vision Problems: Survey on Current Progress, Limitations, and Opportunities—0
SPARK: Self-supervised Personalized Real-time Monocular Face Capture—0
DreamBeast: Distilling 3D Fantastical Animals with Part-Aware Knowledge Transfer—0
DVS: Blood cancer detection using novel CNN-based ensemble approach—0
Reimagining Linear Probing: Kolmogorov-Arnold Networks in Transfer Learning—0
Music auto-tagging in the long tail: A few-shot approach—0
Identification of head impact locations, speeds, and force based on head kinematicsCode0
Deep Learning Techniques for Hand Vein Biometrics: A Comprehensive Review—0
Manifold Learning via Foliations and Knowledge Transfer—0
Deep Neural Network-Based Sign Language Recognition: A Comprehensive Approach Using Transfer Learning with Explainability—0
Distributed Convolutional Neural Network Training on Mobile and Edge Clusters—0
Inference is All You Need: Self Example Retriever for Cross-domain Dialogue State Tracking with ChatGPT—0
A Bayesian Framework for Active Tactile Object Recognition, Pose Estimation and Shape Transfer Learning—0
A comprehensive study on Blood Cancer detection and classification using Convolutional Neural Network—0
Distilling Generative-Discriminative Representations for Very Low-Resolution Face Recognition—0
Adaptive Meta-Domain Transfer Learning (AMDTL): A Novel Approach for Knowledge Transfer in AICode0
Show:102550
← PrevPage 53 of 207Next →
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