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 8776–8800 of 10307 papers

TitleStatusHype
An EfficientNet-based modified sigmoid transform for enhancing dermatological macro-images of melanoma and nevi skin lesionsCode0
An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language ModelsCode0
A Neural Grammatical Error Correction System Built On Better Pre-training and Sequential Transfer LearningCode0
An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning SystemsCode0
A New Dataset for Topic-Based Paragraph Classification in Genocide-Related Court TranscriptsCode0
ANGOFA: Leveraging OFA Embedding Initialization and Synthetic Data for Angolan Language ModelCode0
Animal Detection in Man-made EnvironmentsCode0
An Information-Geometric Distance on the Space of TasksCode0
An Information-Theoretic Metric of Transferability for Task Transfer LearningCode0
An Intrusion Response System utilizing Deep Q-Networks and System PartitionsCode0
An Iterative Multi-Knowledge Transfer Network for Aspect-Based Sentiment AnalysisCode0
AniWho : A Quick and Accurate Way to Classify Anime Character Faces in ImagesCode0
An LSTM Feature Imitation Network for Hand Movement Recognition from sEMG SignalsCode0
ANNA: Abstractive Text-to-Image Synthesis with Filtered News CaptionsCode0
An Open-set Recognition and Few-Shot Learning Dataset for Audio Event Classification in Domestic EnvironmentsCode0
An Optimization Framework for Processing and Transfer Learning for the Brain Tumor SegmentationCode0
An Unsupervised Multiple-Task and Multiple-Teacher Model for Cross-lingual Named Entity RecognitionCode0
Aplicación de redes neuronales convolucionales profundas al diagnóstico asistido de la enfermedad de AlzheimerCode0
Appeal prediction for AI up-scaled ImagesCode0
Application of Facial Recognition using Convolutional Neural Networks for Entry Access ControlCode0
Application of Neural Ordinary Differential Equations for ITER Burning Plasma DynamicsCode0
Transfer Learning for Risk Classification of Social Media Posts: Model Evaluation StudyCode0
Application of Transfer Learning to Sign Language Recognition using an Inflated 3D Deep Convolutional Neural NetworkCode0
Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation TaskCode0
A Practitioners' Guide to Transfer Learning for Text Classification using Convolutional Neural NetworksCode0
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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