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 2626–2650 of 10307 papers

TitleStatusHype
Developing High Quality Training Samples for Deep Learning Based Local Climate Zone Classification in Korea—0
Developmental Bayesian Optimization of Black-Box with Visual Similarity-Based Transfer Learning—0
Balancing Exploration and Exploitation in LLM using Soft RLLF for Enhanced Negation Understanding—0
Balancing Data through Data Augmentation Improves the Generality of Transfer Learning for Diabetic Retinopathy Classification—0
Balancing Accuracy and Training Time in Federated Learning for Violence Detection in Surveillance Videos: A Study of Neural Network Architectures—0
Balanced Semi-Supervised Generative Adversarial Network for Damage Assessment from Low-Data Imbalanced-Class Regime—0
Anatomical Consistency Distillation and Inconsistency Synthesis for Brain Tumor Segmentation with Missing Modalities—0
Additional Positive Enables Better Representation Learning for Medical Images—0
Balanced Multi-modal Federated Learning via Cross-Modal Infiltration—0
Balanced Multi-Factor In-Context Learning for Multilingual Large Language Models—0
An Approach Towards Identifying Bangladeshi Leaf Diseases through Transfer Learning and XAI—0
Anaphoric Zero Pronoun Identification: A Multilingual Approach—0
Balanced Distribution Adaptation for Transfer Learning—0
Additional Look into GAN-based Augmentation for Deep Learning COVID-19 Image Classification—0
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning—0
Developing efficient transfer learning strategies for robust scene recognition in mobile robotics using pre-trained convolutional neural networks—0
DeviceBERT: Applied Transfer Learning With Targeted Annotations and Vocabulary Enrichment to Identify Medical Device and Component Terminology in FDA Recall Summaries—0
Bailong: Bilingual Transfer Learning based on QLoRA and Zip-tie Embedding—0
An analytic theory of generalization dynamics and transfer learning in deep linear networks—0
BadPre: Task-agnostic Backdoor Attacks to Pre-trained NLP Foundation Models—0
An analysis of the transfer learning of convolutional neural networks for artistic images—0
Adding more data does not always help: A study in medical conversation summarization with PEGASUS—0
BactInt: A domain driven transfer learning approach and a corpus for extracting inter-bacterial interactions from biomedical text—0
Background-Foreground Segmentation for Interior Sensing in Automotive Industry—0
A Composite Fault Diagnosis Model for NPPs Based on Bayesian-EfficientNet Module—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