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 9201–9250 of 10307 papers

TitleStatusHype
Hardware Conditioned Policies for Multi-Robot Transfer LearningCode0
Differential Private Stack Generalization with an Application to Diabetes Prediction—0
CNN based dense underwater 3D scene reconstruction by transfer learning using bubble database—0
SpotTune: Transfer Learning through Adaptive Fine-tuningCode0
Artificial Color Constancy via GoogLeNet with Angular Loss FunctionCode0
DNN Transfer Learning from Diversified Micro-Doppler for Motion Classification—0
Modularity in biological evolution and evolutionary computation—0
Can Synthetic Faces Undo the Damage of Dataset Bias to Face Recognition and Facial Landmark Detection?Code0
A Pretrained DenseNet Encoder for Brain Tumor Segmentation—0
Slum Segmentation and Change Detection : A Deep Learning ApproachCode0
Transfer Learning Using Classification Layer Features of CNN—0
Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain AdaptationCode0
Transfer Learning with Deep CNNs for Gender Recognition and Age Estimation—0
Synonym Expansion for Large Shopping Taxonomies—0
Evaluation of deep neural networks for traffic sign detection systemsCode0
Autonomous Extraction of a Hierarchical Structure of Tasks in Reinforcement Learning, A Sequential Associate Rule Mining Approach—0
Not just a matter of semantics: the relationship between visual similarity and semantic similarity—0
Transfer Learning for Mixed-Integer Resource Allocation Problems in Wireless Networks—0
Domain Adaptive Transfer Learning with Specialist Models—0
On Deep Domain Adaptation: Some Theoretical Understandings—0
On Generality and Knowledge Transferability in Cross-Domain Duplicate Question Detection for Heterogeneous Community Question Answering—0
On transfer learning using a MAC model variant—0
MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property PredictionCode0
Controllability, Multiplexing, and Transfer Learning in Networks using Evolutionary LearningCode0
Probabilistic Random Forest: A machine learning algorithm for noisy datasetsCode0
Performance Estimation of Synthesis Flows cross Technologies using LSTMs and Transfer Learning—0
Model-guided Multi-path Knowledge Aggregation for Aerial Saliency Prediction—0
Interactive dimensionality reduction using similarity projections—0
Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent AgentsCode0
A Framework of Transfer Learning in Object Detection for Embedded SystemsCode0
Improving speech emotion recognition via Transformer-based Predictive Coding through transfer learning—0
M2M-GAN: Many-to-Many Generative Adversarial Transfer Learning for Person Re-Identification—0
A Fully Automated System for Sizing Nasal PAP Masks Using Facial Photographs—0
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden NeuronsCode0
Doc2Im: document to image conversion through self-attentive embedding—0
Baselines for Reinforcement Learning in Text Games—0
Analysis of Multilingual Sequence-to-Sequence speech recognition systems—0
Transfer Learning from LDA to BiLSTM-CNN for Offensive Language Detection in Twitter—0
Transfer learning of language-independent end-to-end ASR with language model fusion—0
Micro-Attention for Micro-Expression recognitionCode0
Revealing Fine Structures of the Retinal Receptive Field by Deep Learning Networks—0
Language model integration based on memory control for sequence to sequence speech recognition—0
Learning to Rank Query Graphs for Complex Question Answering over Knowledge GraphsCode0
Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data TasksCode0
Zero-Shot Transfer VQA Dataset—0
Universal Sentence Encoder for English—0
Learning Unsupervised Word Mapping by Maximizing Mean Discrepancy—0
Low-resource named entity recognition via multi-source projection: Not quite there yet?—0
Multilingual NMT with a language-independent attention bridgeCode0
Addressing word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages—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