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 1851–1900 of 10307 papers

TitleStatusHype
CloudifierNet -- Deep Vision Models for Artificial Image Processing—0
CloudRCA: A Root Cause Analysis Framework for Cloud Computing Platforms—0
ChildGAN: Large Scale Synthetic Child Facial Data Using Domain Adaptation in StyleGAN—0
A Point in the Right Direction: Vector Prediction for Spatially-aware Self-supervised Volumetric Representation Learning—0
COVID-19 Detection using Transfer Learning with Convolutional Neural Network—0
CheX-Nomaly: Segmenting Lung Abnormalities from Chest Radiographs using Machine Learning—0
Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition—0
ClusMFL: A Cluster-Enhanced Framework for Modality-Incomplete Multimodal Federated Learning in Brain Imaging Analysis—0
A Physics-preserved Transfer Learning Method for Differential Equations—0
A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica—0
Clustering-based Multitasking Deep Neural Network for Solar Photovoltaics Power Generation Prediction—0
Clustering Markov Decision Processes For Continual Transfer—0
Cluster, Split, Fuse, and Update: Meta-Learning for Open Compound Domain Adaptive Semantic Segmentation—0
CM3T: Framework for Efficient Multimodal Learning for Inhomogeneous Interaction Datasets—0
Chest Disease Detection In X-Ray Images Using Deep Learning Classification Method—0
CMTA: COVID-19 Misinformation Multilingual Analysis on Twitter—0
Affect inTweets: A Transfer Learning Approach—0
Acceleration of Grokking in Learning Arithmetic Operations via Kolmogorov-Arnold Representation—0
CNN-based approach for glaucoma diagnosis using transfer learning and LBP-based data augmentation—0
CNN based dense underwater 3D scene reconstruction by transfer learning using bubble database—0
Action Recognition using Transfer Learning and Majority Voting for CSGO—0
CNN Based Flank Predictor for Quadruped Animal Species—0
COVID-19 Detection Based on Self-Supervised Transfer Learning Using Chest X-Ray Images—0
CNN-based Survival Model for Pancreatic Ductal Adenocarcinoma in Medical Imaging—0
ChemVise: Maximizing Out-of-Distribution Chemical Detection with the Novel Application of Zero-Shot Learning—0
Accelerating Dependency Graph Learning from Heterogeneous Categorical Event Streams via Knowledge Transfer—0
CNN-Transformer Rectified Collaborative Learning for Medical Image Segmentation—0
Coarse-To-Fine And Cross-Lingual ASR Transfer—0
Char-RNN for Word Stress Detection in East Slavic Languages—0
CoCo DistillNet: a Cross-layer Correlation Distillation Network for Pathological Gastric Cancer Segmentation—0
CoCoNet: A Collaborative Convolutional Network—0
Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI—0
A Physics-driven GraphSAGE Method for Physical Process Simulations Described by Partial Differential Equations—0
COVID-19 Detection and Analysis From Lung CT Images using Novel Channel Boosted CNNs—0
Code-Mixed Text to Speech Synthesis under Low-Resource Constraints—0
Covid-19 Detection from Chest X-ray and Patient Metadata using Graph Convolutional Neural Networks—0
CoDo: Contrastive Learning with Downstream Background Invariance for Detection—0
Coefficient Shape Transfer Learning for Functional Linear Regression—0
Coevo: a collaborative design platform with artificial agents—0
A Review of Deep Learning Approaches for Non-Invasive Cognitive Impairment Detection—0
COVID 19 Diagnosis Analysis using Transfer Learning—0
Maze Learning using a Hyperdimensional Predictive Processing Cognitive Architecture—0
A review of sentiment analysis research in Arabic language—0
Cognitive Learning-Aided Multi-Antenna Communications—0
Cognitive simulation models for inertial confinement fusion: Combining simulation and experimental data—0
A review of technical factors to consider when designing neural networks for semantic segmentation of Earth Observation imagery—0
Coherence Modeling Improves Implicit Discourse Relation Recognition—0
Coherent and Consistent Relational Transfer Learning with Autoencoders—0
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm—0
Characterizing and Avoiding Negative Transfer—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