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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8676–8700 of 10307 papers

TitleStatusHype
Plansformer: Generating Symbolic Plans using Transformers—0
Plant Disease Detection from Images—0
Plant Species Classification Using Transfer Learning by Pretrained Classifier VGG-19—0
SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models—0
A Bayesian Framework for Active Tactile Object Recognition, Pose Estimation and Shape Transfer Learning—0
A Deep Value-network Based Approach for Multi-Driver Order Dispatching—0
Plaque Classification in Coronary Arteries from IVOCT Images Using Convolutional Neural Networks and Transfer Learning—0
The Impact of Preprocessing on Deep Representations for Iris Recognition on Unconstrained Environments—0
Plug and Play, Model-Based Reinforcement Learning—0
Pluvio: Assembly Clone Search for Out-of-domain Architectures and Libraries through Transfer Learning and Conditional Variational Information Bottleneck—0
A Bayesian Approach to (Online) Transfer Learning: Theory and Algorithms—0
P-MMEval: A Parallel Multilingual Multitask Benchmark for Consistent Evaluation of LLMs—0
PMT-MAE: Dual-Branch Self-Supervised Learning with Distillation for Efficient Point Cloud Classification—0
PMU measurements based short-term voltage stability assessment of power systems via deep transfer learning—0
Pneumonia Detection in Chest X-Ray Images : Handling Class Imbalance—0
Pneumonia Detection in Chest X-Rays using Neural Networks—0
PNN: A Novel Progressive Neural Network for Fault Classification in Rotating Machinery under Small Dataset Constraint—0
PoE: a Panel of Experts for Generalized Automatic Dialogue Assessment—0
A Deep Transfer Learning Method for Cross-Lingual Natural Language Inference—0
A Deep Transfer Learning-based Edge Computing Method for Home Health Monitoring—0
Point Clouds Are Specialized Images: A Knowledge Transfer Approach for 3D Understanding—0
Point Cloud Segmentation Using Transfer Learning with RandLA-Net: A Case Study on Urban Areas—0
A Deep Reinforcement Learning Approach for Audio-based Navigation and Audio Source Localization in Multi-speaker Environments—0
A Deep Q-Network for the Beer Game: A Deep Reinforcement Learning algorithm to Solve Inventory Optimization Problems—0
A Deep Learning System That Generates Quantitative CT Reports for Diagnosing Pulmonary Tuberculosis—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