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 4751–4800 of 10307 papers

TitleStatusHype
Improving Accuracy of Nonparametric Transfer Learning via Vector Segmentation—0
Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study—0
Improving automatic endoscopic stone recognition using a multi-view fusion approach enhanced with two-step transfer learning—0
Improving BERT with Hybrid Pooling Network and Drop Mask—0
Improving Bias in Facial Attribute Classification: A Combined Impact of KL Divergence induced Loss Function and Dual Attention—0
Improving Botnet Detection with Recurrent Neural Network and Transfer Learning—0
Improving Buoy Detection with Deep Transfer Learning for Mussel Farm Automation—0
Improving Cause-of-Death Classification from Verbal Autopsy Reports—0
Improving classification of Adverse Drug Reactions through Using Sentiment Analysis and Transfer Learning—0
Improving Classification through Weak Supervision in Context-specific Conversational Agent Development for Teacher Education—0
Improving Code Autocompletion with Transfer Learning—0
Improving Commonsense Contingent Reasoning by Pseudo-data and Its Application to the Related Tasks—0
Improving Cross-Lingual Transfer Learning for End-to-End Speech Recognition with Speech Translation—0
Improving Customer Service Chatbots with Attention-based Transfer Learning—0
Improving data sharing and knowledge transfer via the Neuroelectrophysiology Analysis Ontology (NEAO)—0
Improving Device Directedness Classification of Utterances with Semantic Lexical Features—0
Improving ECG-based COVID-19 diagnosis and mortality predictions using pre-pandemic medical records at population-scale—0
Improving Event Coreference Resolution by Learning Argument Compatibility from Unlabeled Data—0
Improving Feature Extraction from Histopathological Images Through A Fine-tuning ImageNet Model—0
Improving filling level classification with adversarial training—0
Improving Generalizability of Extracting Social Determinants of Health Using Large Language Models through Prompt-tuning—0
Improving generalization in reinforcement learning through forked agents—0
Improving Generalization of Transfer Learning Across Domains Using Spatio-Temporal Features in Autonomous Driving—0
Improving Hyperparameter Optimization by Planning Ahead—0
Improving Image Classification Robustness through Selective CNN-Filters Fine-Tuning—0
Improving Japanese semantic-role-labeling performance with transfer learning as case for limited resources of tagged corpora on aggregated language—0
Improving Knowledge Distillation in Transfer Learning with Layer-wise Learning Rates—0
Improving Language and Modality Transfer in Translation by Character-level Modeling—0
Improving Local Air Quality Predictions Using Transfer Learning on Satellite Data and Graph Neural Networks—0
Improving Location-based Thermal Emission Side-Channel Analysis Using Iterative Transfer Learning—0
Improving Machine Reading Comprehension with Single-choice Decision and Transfer Learning—0
Improving Machine Translation of Educational Content via Crowdsourcing—0
Improving Mammography Malignancy Segmentation by Designing the Training Process—0
Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study—0
Improving Multi-fidelity Optimization with a Recurring Learning Rate for Hyperparameter Tuning—0
Improving Multi-label Emotion Classification via Sentiment Classification with Dual Attention Transfer Network—0
Improving Natural-Language-based Audio Retrieval with Transfer Learning and Audio & Text Augmentations—0
Improving Neural Machine Translation by Achieving Knowledge Transfer with Sentence Alignment Learning—0
Improving Neural Machine Translation for Sanskrit-English—0
Improving Neural Machine Translation of Indigenous Languages with Multilingual Transfer Learning—0
Improving neural network predictions of material properties with limited data using transfer learning—0
Improving performance and inference on audio classification tasks using capsule networks—0
Improving performance of CNN to predict likelihood of COVID-19 using chest X-ray images with preprocessing algorithms—0
Improving physics-informed neural networks with meta-learned optimization—0
Improving plant disease classification by adaptive minimal ensembling—0
Improving Polish to English Neural Machine Translation with Transfer Learning: Effects of Data Volume and Language Similarity—0
Improving Polyphonic Sound Event Detection on Multichannel Recordings with the Sørensen-Dice Coefficient Loss and Transfer Learning—0
Improving Pretrained YAMNet for Enhanced Speech Command Detection via Transfer Learning—0
Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma—0
Improving Prostate Cancer Detection with Breast Histopathology Images—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