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 3251–3300 of 10307 papers

TitleStatusHype
Dual Relation Mining Network for Zero-Shot Learning—0
Dual Scale-aware Adaptive Masked Knowledge Distillation for Object Detection—0
Analysis and Prediction of NLP models via Task Embeddings—0
Dual-stream contrastive predictive network with joint handcrafted feature view for SAR ship classification—0
Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages—0
Deep Learning Approach for Large-Scale, Real-Time Quantification of Green Fluorescent Protein-Labeled Biological Samples in Microreactors—0
Automatic Recognition of the Supraspinatus Tendinopathy from Ultrasound Images using Convolutional Neural Networks—0
Analysis and Adaptation of YOLOv4 for Object Detection in Aerial Images—0
Deep Learning Approach Combining Lightweight CNN Architecture with Transfer Learning: An Automatic Approach for the Detection and Recognition of Bangladeshi Banknotes—0
DVS: Blood cancer detection using novel CNN-based ensemble approach—0
Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts—0
Dyn-Adapter: Towards Disentangled Representation for Efficient Visual Recognition—0
Automatic Recognition of Food Ingestion Environment from the AIM-2 Wearable Sensor—0
A Data Augmented Approach to Transfer Learning for Covid-19 Detection—0
Enhancing Non-mass Breast Ultrasound Cancer Classification With Knowledge Transfer—0
Dynamically enhanced static handwriting representation for Parkinson's disease detection—0
Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning—0
Dynamically writing coupled memories using a reinforcement learning agent, meeting physical bounds—0
Anomaly Detection Using Computer Vision: A Comparative Analysis of Class Distinction and Performance Metrics—0
Dynamic Corrective Self-Distillation for Better Fine-Tuning of Pretrained Models—0
Enhancing Performance, Calibration Time and Efficiency in Brain-Machine Interfaces through Transfer Learning and Wearable EEG Technology—0
Automatic Recognition of Coal and Gangue based on Convolution Neural Network—0
Dynamic Ensemble Reasoning for LLM Experts—0
Dynamic Flows on Curved Space Generated by Labeled Data—0
Dynamic Gazetteer Integration in Multilingual Models for Cross-Lingual and Cross-Domain Named Entity Recognition—0
CAKD: A Correlation-Aware Knowledge Distillation Framework Based on Decoupling Kullback-Leibler Divergence—0
Dynamic Indoor Fingerprinting Localization based on Few-Shot Meta-Learning with CSI Images—0
Dynamic Knowledge Distillation for Black-box Hypothesis Transfer Learning—0
Calibrated and Robust Foundation Models for Vision-Language and Medical Image Tasks Under Distribution Shift—0
Dynamic Schema Graph Fusion Network for Multi-Domain Dialogue State Tracking—0
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models—0
Dynamic Schema Graph Fusion Network for Multi-Domain Dialogue State Tracking—0
A Comparison of LSTM and BERT for Small Corpus—0
Dynamic Transfer Learning for Named Entity Recognition—0
Deep learning and high harmonic generation—0
DynaQuant: Compressing Deep Learning Training Checkpoints via Dynamic Quantization—0
CALLIC: Content Adaptive Learning for Lossless Image Compression—0
Advancing 3D Point Cloud Understanding through Deep Transfer Learning: A Comprehensive Survey—0
Early detection of diabetes through transfer learning-based eye (vision) screening and improvement of machine learning model performance and advanced parameter setting algorithms—0
Early Diagnosis and Severity Assessment of Weligama Coconut Leaf Wilt Disease and Coconut Caterpillar Infestation using Deep Learning-based Image Processing Techniques—0
Deep Learning and Health Informatics for Smart Monitoring and Diagnosis—0
Early Diagnosis of Parkinsons Disease by Analyzing Magnetic Resonance Imaging Brain Scans and Patient Characteristics—0
Camera On-boarding for Person Re-identification using Hypothesis Transfer Learning—0
Early Prediction of Sepsis: Feature-Aligned Transfer Learning—0
Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks—0
Enhancing learning in spiking neural networks through neuronal heterogeneity and neuromodulatory signaling—0
Deep Learning Analysis of Cardiac MRI in Legacy Datasets: Multi-Ethnic Study of Atherosclerosis—0
ECAT: A Entire space Continual and Adaptive Transfer Learning Framework for Cross-Domain Recommendation—0
ECAvg: An Edge-Cloud Collaborative Learning Approach using Averaged Weights—0
Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ—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