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 7951–8000 of 10307 papers

TitleStatusHype
Automating the Surveillance of Mosquito Vectors from Trapped Specimens Using Computer Vision Techniques—0
A review of sentiment analysis research in Arabic language—0
Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation—0
Domain Specific, Semi-Supervised Transfer Learning for Medical Imaging—0
A machine learning approach to using Quality-of-Life patient scores in guiding prostate radiation therapy dosing—0
Automatic Discovery of Novel Intents & Domains from Text Utterances—0
Leveraging Text Data Using Hybrid Transformer-LSTM Based End-to-End ASR in Transfer Learning—0
Bridging the gap between Natural and Medical Images through Deep ColorizationCode0
Cross-Domain Few-Shot Learning with Meta Fine-Tuning—0
Learning to Transfer Dynamic Models of Underactuated Soft Robotic Hands—0
Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation—0
Hidden Markov Models and their Application for Predicting Failure Events—0
Classification of Industrial Control Systems screenshots using Transfer Learning—0
Self-supervised Transfer Learning for Instance Segmentation through Physical InteractionCode0
Human Instruction-Following with Deep Reinforcement Learning via Transfer-Learning from Text—0
Cross-lingual Approaches for Task-specific Dialogue Act Recognition—0
Transfer learning based multi-fidelity physics informed deep neural network—0
Information-theoretic analysis for transfer learning—0
Feature Transformation Ensemble Model with Batch Spectral Regularization for Cross-Domain Few-Shot Classification—0
Support-BERT: Predicting Quality of Question-Answer Pairs in MSDN using Deep Bidirectional Transformer—0
FuCiTNet: Improving the generalization of deep learning networks by the fusion of learned class-inherent transformationsCode0
A Deep Learning based Wearable Healthcare IoT Device for AI-enabled Hearing Assistance Automation—0
Neural Entity Linking on Technical Service Tickets—0
KEIS@JUST at SemEval-2020 Task 12: Identifying Multilingual Offensive Tweets Using Weighted Ensemble and Fine-Tuned BERT—0
Temperate Fish Detection and Classification: a Deep Learning based Approach—0
An Evaluation of Recent Neural Sequence Tagging Models in Turkish Named Entity Recognition—0
On Using Transfer Learning For Plant Disease Detection—0
Convolutional Neural Networks for Classifying Melanoma Images—0
Industrial Federated Learning -- Requirements and System Design—0
NIT-Agartala-NLP-Team at SemEval-2020 Task 8: Building Multimodal Classifiers to tackle Internet Humor—0
Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response—0
A network-based transfer learning approach to improve sales forecasting of new products—0
Multi-Channel Transfer Learning of Chest X-ray Images for Screening of COVID-19—0
High-Fidelity Accelerated MRI Reconstruction by Scan-Specific Fine-Tuning of Physics-Based Neural Networks—0
A Framework for Hierarchical Multilingual Machine Translation—0
Segmenting Scientific Abstracts into Discourse Categories: A Deep Learning-Based Approach for Sparse Labeled DataCode0
SciANN: A Keras/Tensorflow wrapper for scientific computations and physics-informed deep learning using artificial neural networks—0
An Inductive Transfer Learning Approach using Cycle-consistent Adversarial Domain Adaptation with Application to Brain Tumor Segmentation—0
On the Generation of Medical Dialogues for COVID-19Code0
A Comparison of Few-Shot Learning Methods for Underwater Optical and Sonar Image Classification—0
Generative Model-driven Structure Aligning Discriminative Embeddings for Transductive Zero-shot Learning—0
Domain-specific loss design for unsupervised physical training: A new approach to modeling medical ML solutions—0
Visually Impaired Aid using Convolutional Neural Networks, Transfer Learning, and Particle Competition and CooperationCode0
Transfer Learning and Online Learning for Traffic Forecasting under Different Data Availability Conditions: Alternatives and Pitfalls—0
Automatic Organization of Neural Modules for Enhanced Collaboration in Neural Networks—0
Relatedness Measures to Aid the Transfer of Building Blocks among Multiple Tasks—0
Planning from Images with Deep Latent Gaussian Process DynamicsCode0
A Multifactorial Optimization Paradigm for Linkage Tree Genetic AlgorithmCode0
Subdomain Adaptation with Manifolds Discrepancy Alignment—0
End-to-end Whispered Speech Recognition with Frequency-weighted Approaches and Pseudo Whisper Pre-training—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