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 4051–4100 of 10307 papers

TitleStatusHype
Evaluating and Improving Child-Directed Automatic Speech Recognition—0
CLCE: An Approach to Refining Cross-Entropy and Contrastive Learning for Optimized Learning Fusion—0
Few-Shot Object Detection via Knowledge Transfer—0
Few-Shot Object Detection with Sparse Context Transformers—0
A Privacy-Preserving Framework with Multi-Modal Data for Cross-Domain Recommendation—0
Adverse Drug Reaction Detection in Twitter Using RoBERTa and Rules—0
Eva-KELLM: A New Benchmark for Evaluating Knowledge Editing of LLMs—0
Class Subset Selection for Transfer Learning using Submodularity—0
\'Etude de l'apprentissage par transfert de syst\`emes de traduction automatique neuronaux (Study on transfer learning in neural machine translation )—0
Few-Shot Transfer Learning for Individualized Braking Intent Detection on Neuromorphic Hardware—0
Class-Specific Data Augmentation: Bridging the Imbalance in Multiclass Breast Cancer Classification—0
Few-shot Unified Question Answering: Tuning Models or Prompts?—0
A Privacy-Preserving Domain Adversarial Federated learning for multi-site brain functional connectivity analysis—0
FEWS: Large-Scale, Low-Shot Word Sense Disambiguation with the Dictionary—0
Ethio-Fake: Cutting-Edge Approaches to Combat Fake News in Under-Resourced Languages Using Explainable AI—0
Class-Specific Channel Attention for Few-Shot Learning—0
Estimating the influence of auxiliary tasks for multi-task learning of sequence tagging tasks—0
Estimating State of Charge for xEV batteries using 1D Convolutional Neural Networks and Transfer Learning—0
Class Similarity-Based Multimodal Classification under Heterogeneous Category Sets—0
Filtered Inner Product Projection for Crosslingual Embedding Alignment—0
A privacy-preserving data storage and service framework based on deep learning and blockchain for construction workers' wearable IoT sensors—0
Filtering DDoS Attacks from Unlabeled Network Traffic Data Using Online Deep Learning—0
Financial Aspect-Based Sentiment Analysis using Deep Representations—0
Finding Answers from the Word of God: Domain Adaptation for Neural Networks in Biblical Question Answering—0
Adversary ML Resilience in Autonomous Driving Through Human Centered Perception Mechanisms—0
Findings of the Covid-19 MLIA Machine Translation Task—0
Finding the Most Transferable Tasks for Brain Image Segmentation—0
Active Learning with Transfer Learning—0
Estimating Q(s,s') with Deterministic Dynamics Gradients—0
Classroom-Inspired Multi-Mentor Distillation with Adaptive Learning Strategies—0
Estimating Posterior Ratio for Classification: Transfer Learning from Probabilistic Perspective—0
Class Relationship Embedded Learning for Source-Free Unsupervised Domain Adaptation—0
A Prior Knowledge Based Tumor and Tumoral Subregion Segmentation Tool for Pediatric Brain Tumors—0
Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery—0
Estimating Bicycle Route Attractivity from Image Data—0
A Primer on Pretrained Multilingual Language Models—0
Adversary Helps: Gradient-based Device-Free Domain-Independent Gesture Recognition—0
Fine-Grained Vehicle Classification with Unsupervised Parts Co-occurrence Learning—0
ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learning—0
Fine-to-coarse Knowledge Transfer For Low-Res Image Classification—0
FINETUNA: Fine-tuning Accelerated Molecular Simulations—0
Fine-tuned Generative Adversarial Network-based Model for Medical Image Super-Resolution—0
Classifying Judgements using Transfer Learning—0
EriBERTa: A Bilingual Pre-Trained Language Model for Clinical Natural Language Processing—0
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning—0
Equitable Skin Disease Prediction Using Transfer Learning and Domain Adaptation—0
Classification of Skin Disease Using Transfer Learning in Convolutional Neural Networks—0
EPUTION at SemEval-2018 Task 2: Emoji Prediction with User Adaption—0
Classification of Skin Cancer Images using Convolutional Neural Networks—0
A Pretrained DenseNet Encoder for Brain Tumor Segmentation—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