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 2401–2425 of 10307 papers

TitleStatusHype
NVS-Adapter: Plug-and-Play Novel View Synthesis from a Single ImageCode1
Open-Pose 3D Zero-Shot Learning: Benchmark and ChallengesCode1
Medical Image Classification Using Transfer Learning and Chaos Game Optimization on the Internet of Medical Things—0
Dynamic Corrective Self-Distillation for Better Fine-Tuning of Pretrained Models—0
Transferring CLIP's Knowledge into Zero-Shot Point Cloud Semantic Segmentation—0
Neural Machine Translation of Clinical Text: An Empirical Investigation into Multilingual Pre-Trained Language Models and Transfer-LearningCode0
Understanding and Leveraging the Learning Phases of Neural Networks—0
Progressive Multi-Modality Learning for Inverse Protein FoldingCode1
Facial Beauty Analysis Using Distribution Prediction and CNN EnsemblesCode0
COVID-19 Detection Using Slices Processing Techniques and a Modified Xception Classifier from Computed Tomography Images—0
Hacking Task Confounder in Meta-LearningCode0
Jumpstarting Surgical Computer Vision—0
Initialization Matters for Adversarial Transfer LearningCode0
Mutual Enhancement of Large and Small Language Models with Cross-Silo Knowledge Transfer—0
Labrador: Exploring the Limits of Masked Language Modeling for Laboratory DataCode1
PGDS: Pose-Guidance Deep Supervision for Mitigating Clothes-Changing in Person Re-IdentificationCode0
Teamwork Dimensions Classification Using BERT—0
Model Evaluation for Domain Identification of Unknown Classes in Open-World Recognition: A Proposal—0
Data Scarcity in Recommendation Systems: A Survey—0
GYM at Qur’an QA 2023 Shared Task: Multi-Task Transfer Learning for Quranic Passage Retrieval and Question Answering with Large Language ModelsCode0
Enhancing Polynomial Chaos Expansion Based Surrogate Modeling using a Novel Probabilistic Transfer Learning Strategy—0
TLCE: Transfer-Learning Based Classifier Ensembles for Few-Shot Class-Incremental Learning—0
Small Area Estimation of Case Growths for Timely COVID-19 Outbreak DetectionCode0
Decoding Working-Memory Load During n-Back Task Performance from High Channel NIRS Data—0
A Scalable and Generalizable Pathloss Map PredictionCode1
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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