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 8951–9000 of 10307 papers

TitleStatusHype
Deep Learning for Large-Scale Real-World ACARS and ADS-B Radio Signal Classification—0
An Evaluation of Transfer Learning for Classifying Sales Engagement Emails at Large Scale—0
ProductNet: a Collection of High-Quality Datasets for Product Representation Learning—0
Convolutional Neural Network and Transfer Learning for High Impedance Fault Detection—0
A Multi-Task Learning Framework for Overcoming the Catastrophic Forgetting in Automatic Speech Recognition—0
Double Transfer Learning for Breast Cancer Histopathologic Image Classification—0
Active Adversarial Domain Adaptation—0
An Empirical Evaluation of Text Representation Schemes on Multilingual Social Web to Filter the Textual Aggression—0
End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learning—0
Digging Deeper into Egocentric Gaze Prediction—0
Deep Transfer Learning for Single-Channel Automatic Sleep Staging with Channel Mismatch—0
Cramnet: Layer-wise Deep Neural Network Compression with Knowledge Transfer from a Teacher Network—0
Scalable Cross-Lingual Transfer of Neural Sentence Embeddings—0
Variational Information Distillation for Knowledge Transfer—0
Weakly-Supervised White and Grey Matter Segmentation in 3D Brain Ultrasound—0
Knowledge Squeezed Adversarial Network Compression—0
Imitating Targets from all sides: An Unsupervised Transfer Learning method for Person Re-identification—0
Fast Enhanced CT Metal Artifact Reduction using Data Domain Deep LearningCode0
A New GAN-based End-to-End TTS Training Algorithm—0
Improving Image Classification Robustness through Selective CNN-Filters Fine-Tuning—0
From Patch to Image Segmentation using Fully Convolutional Networks -- Application to Retinal ImagesCode0
A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer LearningCode0
Heterogeneous Multi-task Metric Learning across Multiple Domains—0
Learned 3D Shape Representations Using Fused Geometrically Augmented Images: Application to Facial Expression and Action Unit Detection—0
Decomposition-Based Transfer Distance Metric Learning for Image Classification—0
Transferring Knowledge Fragments for Learning Distance Metric from A Heterogeneous Domain—0
On The Power of Curriculum Learning in Training Deep NetworksCode0
The Information Complexity of Learning Tasks, their Structure and their Distance—0
A Many Objective Optimization Approach for Transfer Learning in EEG Classification—0
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian OptimizationCode0
Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation—0
Learning Implicit Generative Models by Matching Perceptual Features—0
Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model For Hyperspectral Image Classification—0
Resource Efficient 3D Convolutional Neural NetworksCode0
Transfer Learning for Performance Modeling of Deep Neural Network SystemsCode0
Transfer Learning with Sparse Associative Memories—0
Correlation Congruence for Knowledge DistillationCode0
Stacked Semantic-Guided Network for Zero-Shot Sketch-Based Image Retrieval—0
Understanding the efficacy, reliability and resiliency of computer vision techniques for malware detection and future research directions—0
Cross-lingual transfer learning for spoken language understanding—0
Lautum Regularization for Semi-supervised Transfer Learning—0
Easy Transfer Learning By Exploiting Intra-domain Structures—0
Identifying disease-free chest X-ray images with deep transfer learning—0
Unveiling phase transitions with machine learningCode0
Transfer Learning for Clinical Time Series Analysis using Deep Neural Networks—0
Multitask Soft Option LearningCode0
Creativity Inspired Zero-Shot LearningCode0
Does an LSTM forget more than a CNN? An empirical study of catastrophic forgetting in NLP—0
Cross-Subject Transfer Learning in Human Activity Recognition Systems using Generative Adversarial Networks—0
Local Aggregation for Unsupervised Learning of Visual EmbeddingsCode0
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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