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
Exploring the Efficacy of Transfer Learning in Mining Image-Based Software Artifacts—0
Exploring the flavor structure of leptons via diffusion models—0
A Multimodal Lightweight Approach to Fault Diagnosis of Induction Motors in High-Dimensional Dataset—0
FiGKD: Fine-Grained Knowledge Distillation via High-Frequency Detail Transfer—0
DEEGITS: Deep Learning based Framework for Measuring Heterogenous Traffic State in Challenging Traffic Scenarios—0
Exploring the Limits of Transfer Learning with Unified Model in the Cybersecurity Domain—0
Automated Visual Attention Detection using Mobile Eye Tracking in Behavioral Classroom Studies—0
Automated Tomato Maturity Estimation Using an Optimized Residual Model with Pruning and Quantization Techniques—0
Exploring the Optimization Objective of One-Class Classification for Anomaly Detection—0
Are We Ready for Out-of-Distribution Detection in Digital Pathology?—0
Exploring the Power of Pure Attention Mechanisms in Blind Room Parameter Estimation—0
Collaborative Group Learning—0
Collaborative Knowledge Fusion: A Novel Approach for Multi-task Recommender Systems via LLMs—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
Decouple Non-parametric Knowledge Distillation For End-to-end Speech Translation—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
A Multi-Modal Knowledge-Enhanced Framework for Vessel Trajectory Prediction—0
FGLP: A Federated Fine-Grained Location Prediction System for Mobile Users—0
Collaborative Teacher-Student Learning via Multiple Knowledge Transfer—0
Exploring Transfer Learning for Urdu Speech Synthesis—0
Figure Eight at SemEval-2019 Task 3: Ensemble of Transfer Learning Methods for Contextual Emotion Detection—0
Automated Testing of Spatially-Dependent Environmental Hypotheses through Active Transfer Learning—0
A Compare-Aggregate Model with Latent Clustering for Answer Selection—0
Decoupled classifiers for fair and efficient machine learning—0
Exploring Vision Transformers for 3D Human Motion-Language Models with Motion Patches—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
Expressive Power of Randomized Signature—0
Decoupled Box Proposal and Featurization with Ultrafine-Grained Semantic Labels Improve Image Captioning and Visual Question Answering—0
Colorectal cancer diagnosis from histology images: A comparative study—0
Extending Multilingual BERT to Low-Resource Languages—0
A Multimodal German Dataset for Automatic Lip Reading Systems and Transfer Learning—0
Using LLMs to Establish Implicit User Sentiment of Software Desirability—0
Decomposition-Based Transfer Distance Metric Learning for Image Classification—0
External knowledge transfer deployment inside a simple double agent Viterbi algorithm—0
A Multi-media Approach to Cross-lingual Entity Knowledge Transfer—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
Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media—0
Extraction of Key-frames of Endoscopic Videos by using Depth Information—0
Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution—0
Extreme Low Resolution Activity Recognition with Confident Spatial-Temporal Attention Transfer—0
Decomposed Cross-modal Distillation for RGB-based Temporal Action Detection—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