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 8601–8650 of 10307 papers

TitleStatusHype
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
CMTA: COVID-19 Misinformation Multilingual Analysis on Twitter—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
CNN Based Detection of Cardiovascular Diseases from ECG Images—0
CNN Based Flank Predictor for Quadruped Animal Species—0
CNN-based Survival Model for Pancreatic Ductal Adenocarcinoma in Medical Imaging—0
CNN-LSTM and Transfer Learning Models for Malware Classification based on Opcodes and API Calls—0
CNN-Transformer Rectified Collaborative Learning for Medical Image Segmentation—0
Coarse-To-Fine And Cross-Lingual ASR Transfer—0
Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network—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
Code-Mixed Text to Speech Synthesis under Low-Resource Constraints—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
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning—0
Maze Learning using a Hyperdimensional Predictive Processing Cognitive Architecture—0
Cognitive Learning-Aided Multi-Antenna Communications—0
Cognitive simulation models for inertial confinement fusion: Combining simulation and experimental data—0
Coherence Modeling Improves Implicit Discourse Relation Recognition—0
Coherent and Consistent Relational Transfer Learning with Autoencoders—0
CoLI-Machine Learning Approaches for Code-mixed Language Identification at the Word Level in Kannada-English Texts—0
Collaborative Adversarial Learning for RelationalLearning on Multiple Bipartite Graphs—0
Collaborative Group Learning—0
Collaborative Knowledge Fusion: A Novel Approach for Multi-task Recommender Systems via LLMs—0
Learning with Shared Representations: Statistical Rates and Efficient Algorithms—0
Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control—0
Collaborative Pressure Ulcer Prevention: An Automated Skin Damage and Pressure Ulcer Assessment Tool for Nursing Professionals, Patients, Family Members and Carers—0
Collaborative Recommendation with Auxiliary Data: A Transfer Learning View—0
Collaborative Teacher-Student Learning via Multiple Knowledge Transfer—0
Collective Knowledge Graph Completion with Mutual Knowledge Distillation—0
Collective Wisdom: Improving Low-resource Neural Machine Translation using Adaptive Knowledge Distillation—0
Collusion Detection with Graph Neural Networks—0
Colorectal cancer diagnosis from histology images: A comparative study—0
Color Enhancement for V-PCC Compressed Point Cloud via 2D Attribute Map Optimization—0
Combating Uncertainty with Novel Losses for Automatic Left Atrium Segmentation—0
Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media—0
Combination of multiple neural networks using transfer learning and extensive geometric data augmentation for assessing cellularity scores in histopathology images—0
Transfer-Recursive-Ensemble Learning for Multi-Day COVID-19 Prediction in India using Recurrent Neural Networks—0
Combined Peak Reduction and Self-Consumption Using Proximal Policy Optimization—0
Combined Scaling for Zero-shot Transfer Learning—0
Combinets: Creativity via Recombination of Neural Networks—0
Combining Behaviors with the Successor Features Keyboard—0
Combining Convolution and Recursive Neural Networks for Sentiment Analysis—0
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification—0
Combining Federated Learning and Control: A Survey—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