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 2251–2275 of 10307 papers

TitleStatusHype
Bridging Domain Gap for Flight-Ready Spaceborne Vision—0
An Investigation of Transfer Learning-Based Sentiment Analysis in Japanese—0
A Quantile-based Approach for Hyperparameter Transfer Learning—0
DeepBeat: A multi-task deep learning approach to assess signal quality and arrhythmia detection in wearable devices—0
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning—0
Deep cross-domain building extraction for selective depth estimation from oblique aerial imagery—0
Deep Ensembling for Perceptual Image Quality Assessment—0
Bridging Classical and Quantum Machine Learning: Knowledge Transfer From Classical to Quantum Neural Networks Using Knowledge Distillation—0
An Investigation of Feature Selection and Transfer Learning for Writer-Independent Offline Handwritten Signature Verification—0
Bridge the Gap Between Visual and Linguistic Comprehension for Generalized Zero-shot Semantic Segmentation—0
Advanced Arabic Alphabet Sign Language Recognition Using Transfer Learning and Transformer Models—0
A Copula approach for hyperparameter transfer learning—0
BridgeNets: Student-Teacher Transfer Learning Based on Recursive Neural Networks and its Application to Distant Speech Recognition—0
Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfer—0
An introduction to domain adaptation and transfer learning—0
An Intrinsically Knowledge-Transferring Developmental Spiking Neural Network for Tactile Classification—0
Adult Glioma Segmentation in Sub-Saharan Africa using Transfer Learning on Stratified Finetuning Data—0
ABSent: Cross-Lingual Sentence Representation Mapping with Bidirectional GANs—0
Deep 3D Face Identification—0
An Interpretable Neural Network with Topical Information for Relevant Emotion Ranking—0
Decouple Non-parametric Knowledge Distillation For End-to-end Speech Translation—0
Breast mass detection in digital mammography based on anchor-free architecture—0
An Interpretable Knowledge Transfer Model for Knowledge Base Completion—0
ADU-Depth: Attention-based Distillation with Uncertainty Modeling for Depth Estimation—0
Breast Lump Detection and Localization with a Tactile Glove Using Deep Learning—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