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 3801–3850 of 10307 papers

TitleStatusHype
Exo2EgoDVC: Dense Video Captioning of Egocentric Procedural Activities Using Web Instructional Videos—0
Exploring the flavor structure of leptons via diffusion models—0
EXIT: An EXplicit Interest Transfer Framework for Cross-Domain Recommendation—0
Close Yet Distinctive Domain Adaptation—0
Examining the behaviour of state-of-the-art convolutional neural networks for brain tumor detection with and without transfer learning—0
EvoSampling: A Granular Ball-based Evolutionary Hybrid Sampling with Knowledge Transfer for Imbalanced Learning—0
A Feature Extraction based Model for Hate Speech Identification—0
Active Semi-supervised Transfer Learning (ASTL) for Offline BCI Calibration—0
Evolving Image Compositions for Feature Representation Learning—0
Evolution of transfer learning in natural language processing—0
Exploring the Power of Pure Attention Mechanisms in Blind Room Parameter Estimation—0
Evolution of ReID: From Early Methods to LLM Integration—0
Evolutionary Multitasking with Solution Space Cutting for Point Cloud Registration—0
Exploring the structure-property relations of thin-walled, 2D extruded lattices using neural networks—0
Exploring the Transferability of a Foundation Model for Fundus Images: Application to Hypertensive Retinopathy—0
A Question Answering Based Pipeline for Comprehensive Chinese EHR Information Extraction—0
Exploring the Uncertainty Properties of Neural Networks’ Implicit Priors in the Infinite-Width Limit—0
Exploring the Uncertainty Properties of Neural Networks' Implicit Priors in the Infinite-Width Limit—0
Exploring the Use of Contrastive Language-Image Pre-Training for Human Posture Classification: Insights from Yoga Pose Analysis—0
Exploring the Viability of Synthetic Query Generation for Relevance Prediction—0
Exploring Transfer Learning and Domain Data Selection for the Biomedical Translation—0
Exploring transfer learning for Deep NLP systems on rarely annotated languages—0
Evolutionary Gait Transfer of Multi-Legged Robots in Complex Terrains—0
Evolutionary Dynamic Multi-objective Optimization Via Regression Transfer Learning—0
CLIP-S4: Language-Guided Self-Supervised Semantic Segmentation—0
Evolutionary Algorithms in the Light of SGD: Limit Equivalence, Minima Flatness, and Transfer Learning—0
Evolutionary Algorithms Approach For Search Based On Semantic Document Similarity—0
CLIP-S^4: Language-Guided Self-Supervised Semantic Segmentation—0
A QUBO Framework for Team Formation—0
Evidence-empowered Transfer Learning for Alzheimer's Disease—0
Everything old is new again: A multi-view learning approach to learning using privileged information and distillation—0
Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits—0
Exposing Computer Generated Images by Using Deep Convolutional Neural Networks—0
Exposing the limits of Zero-shot Cross-lingual Hate Speech Detection—0
Everything is a Video: Unifying Modalities through Next-Frame Prediction—0
Event USKT : U-State Space Model in Knowledge Transfer for Event Cameras—0
CLIP is Almost All You Need: Towards Parameter-Efficient Scene Text Retrieval without OCR—0
Extending Multilingual BERT to Low-Resource Languages—0
A Quantum Neural Network Transfer-Learning Model for Forecasting Problems with Continuous and Discrete Variables—0
A fast general thermal simulation model based on MultiBranch Physics-Informed deep operator neural network—0
Active Reinforcement Learning -- A Roadmap Towards Curious Classifier Systems for Self-Adaptation—0
Event Extraction in Basque: Typologically motivated Cross-Lingual Transfer-Learning Analysis—0
EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition—0
Extracting Events from Industrial Incident Reports—0
Extracting Pasture Phenotype and Biomass Percentages using Weakly Supervised Multi-target Deep Learning on a Small Dataset—0
Event Camera Data Pre-training—0
Event Camera Data Dense Pre-training—0
Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution—0
Extreme Low Resolution Activity Recognition with Confident Spatial-Temporal Attention Transfer—0
CLIP-FLow: Contrastive Learning by semi-supervised Iterative Pseudo labeling for Optical Flow Estimation—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