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 7451–7500 of 10307 papers

TitleStatusHype
A Computational Approach to Understand Mental Health from Reddit: Knowledge-aware Multitask Learning Framework—0
A Computational Model of Inclusive Pedagogy: From Understanding to Application—0
A Computer Vision Application for Assessing Facial Acne Severity from Selfie Images—0
A Computer Vision Approach to Combat Lyme Disease—0
A Computer Vision Approach to Estimate the Localized Sea State—0
A computer vision-based model for occupancy detection using low-resolution thermal images—0
A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review—0
A Concise Review of Transfer Learning—0
A Copula approach for hyperparameter transfer learning—0
A Quantile-based Approach for Hyperparameter Transfer Learning—0
A Corpus for Commonsense Inference in Story Cloze Test—0
A Correlation-Ratio Transfer Learning and Variational Stein's Paradox—0
Acoustic and linguistic representations for speech continuous emotion recognition in call center conversations—0
Acoustic Anomaly Detection for Machine Sounds based on Image Transfer Learning—0
Acoustic Signal Analysis with Deep Neural Network for Detecting Fault Diagnosis in Industrial Machines—0
Acquiring and Adapting Priors for Novel Tasks via Neural Meta-Architectures—0
A Cross-City Federated Transfer Learning Framework: A Case Study on Urban Region Profiling—0
Cross-Modal Distillation for RGB-Depth Person Re-Identification—0
Acted vs. Improvised: Domain Adaptation for Elicitation Approaches in Audio-Visual Emotion Recognition—0
ActiLabel: A Combinatorial Transfer Learning Framework for Activity Recognition—0
A CT Image Classification Network Framework for Lung Tumors Based on Pre-trained MobileNetV2 Model and Transfer learning, And Its Application and Market Analysis in the Medical field—0
Actionable Phrase Detection using NLP—0
Action Learning for 3D Point Cloud Based Organ Segmentation—0
Action Recognition for American Sign Language—0
Action Recognition using Transfer Learning and Majority Voting for CSGO—0
Active Adversarial Domain Adaptation—0
Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation—0
Active flow control for three-dimensional cylinders through deep reinforcement learning—0
Active Learning Approaches to Enhancing Neural Machine Translation—0
Active Learning for Rumor Identification on Social Media—0
Active Learning for Sequence Tagging with Deep Pre-trained Models and Bayesian Uncertainty Estimates—0
Active Learning of Ordinal Embeddings: A User Study on Football Data—0
Active Learning with Transfer Learning—0
Active Multitask Learning with Committees—0
Active Multitask Learning with Committees—0
Active Reinforcement Learning -- A Roadmap Towards Curious Classifier Systems for Self-Adaptation—0
Active Semi-supervised Transfer Learning (ASTL) for Offline BCI Calibration—0
Active Sentiment Domain Adaptation—0
Active shooter detection and robust tracking utilizing supplemental synthetic data—0
Active Transfer Learning for Persian Offline Signature Verification—0
Active Transfer Learning Network: A Unified Deep Joint Spectral-Spatial Feature Learning Model For Hyperspectral Image Classification—0
Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks—0
ActivityCLIP: Enhancing Group Activity Recognition by Mining Complementary Information from Text to Supplement Image Modality—0
Activity Recognition and Prediction in Real Homes—0
Actor Critic with Differentially Private Critic—0
AdaFilter: Adaptive Filter Fine-tuning for Deep Transfer Learning—0
Boosting-GNN: Boosting Algorithm for Graph Networks on Imbalanced Node Classification—0
Adam Mickiewicz University’s English-Hausa Submissions to the WMT 2021 News Translation Task—0
AdapNet: Adaptability Decomposing Encoder-Decoder Network for Weakly Supervised Action Recognition and Localization—0
Adaptable Automation with Modular Deep Reinforcement Learning and Policy 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