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

Showing 28512900 of 10307 papers

TitleStatusHype
Global Neural Networks and The Data Scaling Effect in Financial Time Series ForecastingCode0
Graph Self-Contrast Representation Learning0
Building a Winning Team: Selecting Source Model Ensembles using a Submodular Transferability Estimation Approach0
A Survey of the Impact of Self-Supervised Pretraining for Diagnostic Tasks with Radiological Images0
Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained ModelsCode0
SKoPe3D: A Synthetic Dataset for Vehicle Keypoint Perception in 3D from Traffic Monitoring Cameras0
Transfer Learning between Motor Imagery Datasets using Deep Learning -- Validation of Framework and Comparison of DatasetsCode0
Active flow control for three-dimensional cylinders through deep reinforcement learning0
Deep Learning Approach for Large-Scale, Real-Time Quantification of Green Fluorescent Protein-Labeled Biological Samples in Microreactors0
User lung cancer classification using efficientnet from ct scan images0
Knowledge Graph Embeddings for Multi-Lingual Structured Representations of Radiology Reports0
QS-TTS: Towards Semi-Supervised Text-to-Speech Synthesis via Vector-Quantized Self-Supervised Speech Representation LearningCode1
Exploring Cross-Cultural Differences in English Hate Speech Annotations: From Dataset Construction to AnalysisCode0
Towards Optimal Patch Size in Vision Transformers for Tumor SegmentationCode0
Multi-Transfer Learning Techniques for Detecting Auditory Brainstem Response0
Document AI: A Comparative Study of Transformer-Based, Graph-Based Models, and Convolutional Neural Networks For Document Layout AnalysisCode1
Target PCA: Transfer Learning Large Dimensional Panel Data0
On the Steganographic Capacity of Selected Learning Models0
A General-Purpose Self-Supervised Model for Computational PathologyCode1
Exploring Model Transferability through the Lens of Potential EnergyCode0
Uncovering the Hidden Cost of Model CompressionCode0
Do the Frankenstein, or how to achieve better out-of-distribution performance with manifold mixing model soup0
Robust Activity Recognition for Adaptive Worker-Robot Interaction using Transfer Learning0
LAC: Latent Action Composition for Skeleton-based Action Segmentation0
UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and MemoryCode1
PanoSwin: a Pano-style Swin Transformer for Panorama Understanding0
Attention-Guided Lidar Segmentation and Odometry Using Image-to-Point Cloud Saliency TransferCode0
Comprehensive performance comparison among different types of features in data-driven battery state of health estimation0
Exploring the Transfer Learning Capabilities of CLIP in Domain Generalization for Diabetic RetinopathyCode1
Revolutionizing Disease Diagnosis: A Microservices-Based Architecture for Privacy-Preserving and Efficient IoT Data Analytics Using Federated Learning0
Transfer Learning for Microstructure Segmentation with CS-UNet: A Hybrid Algorithm with Transformer and CNN EncodersCode1
Privacy-Enhanced Zero-Shot Learning via Data-Free Knowledge TransferCode0
An Ensemble Approach to Personalized Real Time Predictive Writing for Experts0
RestNet: Boosting Cross-Domain Few-Shot Segmentation with Residual Transformation NetworkCode1
Mesh-Wise Prediction of Demographic Composition from Satellite Images Using Multi-Head Convolutional Neural Network0
CEIMVEN: An Approach of Cutting Edge Implementation of Modified Versions of EfficientNet (V1-V2) Architecture for Breast Cancer Detection and Classification from Ultrasound ImagesCode0
Heterogeneous Federated Learning via Personalized Generative Networks0
Enhanced Mortality Prediction In Patients With Subarachnoid Haemorrhage Using A Deep Learning Model Based On The Initial CT Scan0
Ultrafast-and-Ultralight ConvNet-Based Intelligent Monitoring System for Diagnosing Early-Stage Mpox Anytime and Anywhere0
Multitasking Evolutionary Algorithm Based on Adaptive Seed Transfer for Combinatorial Problem0
Parameter-Efficient Transfer Learning for Remote Sensing Image-Text RetrievalCode1
Motion-Guided Masking for Spatiotemporal Representation Learning0
Source-Free Collaborative Domain Adaptation via Multi-Perspective Feature Enrichment for Functional MRI AnalysisCode0
E(3)-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement LearningCode1
Self-Supervised Learning for Endoscopic Video AnalysisCode1
Exploring the Optimization Objective of One-Class Classification for Anomaly Detection0
Efficient and Flexible Neural Network Training through Layer-wise Feedback PropagationCode1
Efficient Transfer Learning in Diffusion Models via Adversarial Noise0
Addressing Dynamic and Sparse Qualitative Data: A Hilbert Space Embedding of Categorical Variables0
Knowledge-Aware Prompt Tuning for Generalizable Vision-Language Models0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2Unverified
2DFA-ENTAccuracy69.2Unverified
3DFA-SAFNAccuracy69.1Unverified
4EasyTLAccuracy63.3Unverified
5MEDAAccuracy60.3Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95Unverified