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 8651–8700 of 10307 papers

TitleStatusHype
Combining General and Personalized Models for Epilepsy Detection with Hyperdimensional Computing—0
Combining human parsing with analytical feature extraction and ranking schemes for high-generalization person reidentification—0
Combining Image Features and Patient Metadata to Enhance Transfer Learning—0
Combining Sequence Distillation and Transfer Learning for Efficient Low-Resource Neural Machine Translation Models—0
Open-Ended Fine-Grained 3D Object Categorization by Combining Shape and Texture Features in Multiple Colorspaces—0
Training Data Independent Image Registration With GANs Using Transfer Learning And Segmentation Information—0
Combining Weakly Supervised ML Techniques for Low-Resource NLU—0
Come hither or go away? Recognising pre-electoral coalition signals in the news—0
Command-line Risk Classification using Transformer-based Neural Architectures—0
CommonCanvas: Open Diffusion Models Trained on Creative-Commons Images—0
Commonsense Knowledge Transfer for Pre-trained Language Models—0
Commonsense Knowledge Transfer for Pre-trained Language Models—0
Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface—0
Community-based Multi-Agent Reinforcement Learning with Transfer and Active Exploration—0
Comparative Analysis of Deep Learning Models for Crop Disease Detection: A Transfer Learning Approach—0
Comparative Analysis of Imbalanced Malware Byteplot Image Classification using Transfer Learning—0
Comparative Analysis of Lightweight Deep Learning Models for Memory-Constrained Devices—0
Comparative Analysis of Modality Fusion Approaches for Audio-Visual Person Identification and Verification—0
Comparative Analysis of Transfer Learning in Deep Learning Text-to-Speech Models on a Few-Shot, Low-Resource, Customized Dataset—0
Comparative Evaluation of Transfer Learning for Classification of Brain Tumor Using MRI—0
Comparing Male Nyala and Male Kudu Classification using Transfer Learning with ResNet-50 and VGG-16—0
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark—0
Comparing Unsupervised Word Translation Methods Step by Step—0
Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification—0
Comparison of different CNNs for breast tumor classification from ultrasound images—0
Comparison of fine-tuning strategies for transfer learning in medical image classification—0
Comparison of Neural Models for X-ray Image Classification in COVID-19 Detection—0
Comparison of self-supervised in-domain and supervised out-domain transfer learning for bird species recognition—0
Comparison of Semantic Segmentation Approaches for Horizon/Sky Line Detection—0
Comparison of semi-supervised learning methods for High Content Screening quality control—0
Comparison of Transfer Learning based Additive Manufacturing Models via A Case Study—0
Compiler Provenance Recovery for Multi-CPU Architectures Using a Centrifuge Mechanism—0
Complete Multilingual Neural Machine Translation—0
Complying with the EU AI Act: Innovations in Explainable and User-Centric Hand Gesture Recognition—0
Composable Sparse Fine-Tuning for Cross-Lingual Transfer—0
Composing Task-Agnostic Policies with Deep Reinforcement Learning—0
Time-Frequency Analysis based Deep Interference Classification for Frequency Hopping System—0
Compositional Models: Multi-Task Learning and Knowledge Transfer with Modular Networks—0
Compositional Zero-Shot Domain Transfer with Text-to-Text Models—0
Comprehensive and Comparative Analysis between Transfer Learning and Custom Built VGG and CNN-SVM Models for Wildfire Detection—0
Comprehensive Lung Disease Detection Using Deep Learning Models and Hybrid Chest X-ray Data with Explainable AI—0
Comprehensive performance comparison among different types of features in data-driven battery state of health estimation—0
Compression of Higher Order Ambisonics with Multichannel RVQGAN—0
Computational strategies for cross-species knowledge transfer and translational biomedicine—0
Computation and Data Efficient Backdoor Attacks—0
Compute- and Memory-Efficient Reinforcement Learning with Latent Experience Replay—0
Computer-aided Diagnosis of Malaria through Transfer Learning using the ResNet50 Backbone—0
Computer-Aided Extraction of Select MRI Markers of Cerebral Small Vessel Disease: A Systematic Review—0
Computer-Aided Osteoporosis Diagnosis Using Transfer Learning with Enhanced Features from Stacked Deep Learning Modules—0
Computer Vision in the Food Industry: Accurate, Real-time, and Automatic Food Recognition with Pretrained MobileNetV2—0
Show:102550
← PrevPage 174 of 207Next →
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