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 2401–2450 of 10307 papers

TitleStatusHype
BIOWISH: Biometric Recognition using Wearable Inertial Sensors detecting Heart Activity—0
A Deep Q-Network for the Beer Game: A Deep Reinforcement Learning algorithm to Solve Inventory Optimization Problems—0
DeePref: Deep Reinforcement Learning For Video Prefetching In Content Delivery Networks—0
A New Channel Boosted Convolutional Neural Network using Transfer Learning—0
BioNCERE: Non-Contrastive Enhancement For Relation Extraction In Biomedical Texts—0
Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation—0
A Deep Learning System That Generates Quantitative CT Reports for Diagnosing Pulmonary Tuberculosis—0
Deep Reinforcement Active Learning for Human-in-the-Loop Person Re-Identification—0
Bio-Measurements Estimation and Support in Knee Recovery through Machine Learning—0
Biological neurons act as generalization filters in reservoir computing—0
A Deep Learning Study on Osteosarcoma Detection from Histological Images—0
FE-Adapter: Adapting Image-based Emotion Classifiers to Videos—0
Transfer Learning with Edge Attention for Prostate MRI Segmentation—0
Biologically inspired sleep algorithm for artificial neural networks—0
BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network—0
BioBERTpt - A Portuguese Neural Language Model for Clinical Named Entity Recognition—0
BioAMA: Towards an End to End BioMedical Question Answering System—0
An Evaluation of Recent Neural Sequence Tagging Models in Turkish Named Entity Recognition—0
A Deep Learning Sequential Decoder for Transient High-Density Electromyography in Hand Gesture Recognition Using Subject-Embedded Transfer Learning—0
Deep Reinforcement Learning Based Cross-Layer Design in Terahertz Mesh Backhaul Networks—0
Semi-Supervised Domain Adaptation with Representation Learning for Semantic Segmentation across Time—0
An Evaluation of Progressive Neural Networksfor Transfer Learning in Natural Language Processing—0
BiNet: Degraded-Manuscript Binarization in Diverse Document Textures and Layouts using Deep Encoder-Decoder Networks—0
A Deep Learning Perspective on the Origin of Facial Expressions—0
Binary Paragraph Vectors—0
Binary Classification of Alzheimer Disease using sMRI Imaging modality and Deep Learning—0
An evaluation of pre-trained models for feature extraction in image classification—0
Deep Neural Networks to Enable Real-time Multimessenger Astrophysics—0
Bilingual Transfer Learning for Online Product Classification—0
Bilingual Language Modeling, A transfer learning technique for Roman Urdu—0
A neural network to classify metaphorical violence on cable news—0
Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition—0
A Neural Network Model for Part-Of-Speech Tagging of Social Media Texts—0
A Deep Learning Method for Complex Human Activity Recognition Using Virtual Wearable Sensors—0
DeepONet as a Multi-Operator Extrapolation Model: Distributed Pretraining with Physics-Informed Fine-Tuning—0
Bilinear classifiers for visual recognition—0
Bi-level Unbalanced Optimal Transport for Partial Domain Adaptation—0
A Neural Network Based Method with Transfer Learning for Genetic Data Analysis—0
A Comprehensive Survey on Source-free Domain Adaptation—0
A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability—0
Machine Learning Applications in Medical Prognostics: A Comprehensive Review—0
BIGSAGE: unsupervised inductive representation learning of graph via bi-attended sampling and global-biased aggregating—0
Bi-Directional Semi-Supervised Training of Convolutional Neural Networks for Ultrasound Elastography Displacement Estimation—0
An Euler-based GAN for time series—0
Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation—0
Bidirectional Language Models Are Also Few-shot Learners—0
A network-based transfer learning approach to improve sales forecasting of new products—0
Deep Q-Learning with Q-Matrix Transfer Learning for Novel Fire Evacuation Environment—0
Bidirectional Brain Image Translation using Transfer Learning from Generic Pre-trained Models—0
Bibliometric-enhanced Information Retrieval: 2nd International BIR Workshop—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