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 2651–2700 of 10307 papers

TitleStatusHype
Backdoor Attacks against Transfer Learning with Pre-trained Deep Learning Models—0
An Analysis of RF Transfer Learning Behavior Using Synthetic Data—0
A 3M-Hybrid Model for the Restoration of Unique Giant Murals: A Case Study on the Murals of Yongle Palace—0
An Evaluation of Transfer Learning for Classifying Sales Engagement Emails at Large Scale—0
Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition—0
Baby Physical Safety Monitoring in Smart Home Using Action Recognition System—0
An Analysis of Encoder Representations in Transformer-Based Machine Translation—0
BabyNet: Reconstructing 3D faces of babies from uncalibrated photographs—0
A Zero-Shot Learning Approach for Ephemeral Gully Detection from Remote Sensing using Vision Language Models—0
An analysis of data variation and bias in image-based dermatological datasets for machine learning classification—0
Ada-VSR: Adaptive Video Super-Resolution with Meta-Learning—0
A Zero-Shot Generalization Framework for LLM-Driven Cross-Domain Sequential Recommendation—0
A Named Entity Recognition Shootout for German—0
A white-box analysis on the writer-independent dichotomy transformation applied to offline handwritten signature verification—0
Analyzing Urdu Social Media for Sentiments using Transfer Learning with Controlled Translations—0
AdaVocoder: Adaptive Vocoder for Custom Voice—0
A Complete Recipe for Bayesian Knowledge Transfer: Object Tracking—0
Digital Fingerprinting of Microstructures—0
AdaTrans: Feature-wise and Sample-wise Adaptive Transfer Learning for High-dimensional Regression—0
Analyzing the Variations in Emergency Department Boarding and Testing the Transferability of Forecasting Models across COVID-19 Pandemic Waves in Hong Kong: Hybrid CNN-LSTM approach to quantifying building-level socioecological risk—0
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting—0
Avoid Forgetting by Preserving Global Knowledge Gradients in Federated Learning with Non-IID Data—0
Analyzing the Forgetting Problem in Pretrain-Finetuning of Open-domain Dialogue Response Models—0
DiFuse-Net: RGB and Dual-Pixel Depth Estimation using Window Bi-directional Parallax Attention and Cross-modal Transfer Learning—0
A visual encoding model based on deep neural networks and transfer learning—0
Analyzing the Evaluation of Cross-Lingual Knowledge Transfer in Multilingual Language Models—0
Analyzing the Effect of Multi-task Learning for Biomedical Named Entity Recognition—0
A vision transformer-based framework for knowledge transfer from multi-modal to mono-modal lymphoma subtyping models—0
A3CLNN: Spatial, Spectral and Multiscale Attention ConvLSTM Neural Network for Multisource Remote Sensing Data Classification—0
DIGEST: Deeply supervIsed knowledGE tranSfer neTwork learning for brain tumor segmentation with incomplete multi-modal MRI scans—0
A Vision-based Solution for Track Misalignment Detection—0
A View Independent Classification Framework for Yoga Postures—0
A Dataset of Offensive Language in Kosovo Social Media—0
Analyzing Learned Convnet Features with Dirichlet Process Gaussian Mixture Models—0
Deep Learning for Screening COVID-19 using Chest X-Ray Images—0
Deep Learning for Radio Resource Allocation with Diverse Quality-of-Service Requirements in 5G—0
A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation—0
Deep Learning for Over-the-Air Non-Orthogonal Signal Classification—0
Deep Learning for Motion Classification in Ankle Exoskeletons Using Surface EMG and IMU Signals—0
Analyzing Knowledge Transfer in Deep Q-Networks for Autonomously Handling Multiple Intersections—0
Deep learning for model correction of dynamical systems with data scarcity—0
Deep Learning for Lung Disease Classification Using Transfer Learning and a Customized CNN Architecture with Attention—0
A Dataset for Sanskrit Word Segmentation—0
Deep Learning for Large-Scale Real-World ACARS and ADS-B Radio Signal Classification—0
Deep Learning for identifying radiogenomic associations in breast cancer—0
Auxiliary Input in Training: Incorporating Catheter Features into Deep Learning Models for ECG-Free Dynamic Coronary Roadmapping—0
Analyzing Customer Feedback for Product Fit Prediction—0
Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks—0
Deep Learning in Earthquake Engineering: A Comprehensive Review—0
Model-Based and Data-Driven Strategies in Medical Image Computing—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