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 6476–6500 of 10307 papers

TitleStatusHype
Indoor Positioning via Gradient Boosting Enhanced with Feature Augmentation using Deep Learning—0
Semisupervised Adversarial Neural Networks for Cyber Security Transfer Learning—0
Semi-supervised and Transfer learning approaches for low resource sentiment classification—0
Application of Transfer Learning Approaches in Multimodal Wearable Human Activity Recognition—0
Induction of Subgoal Automata for Reinforcement Learning—0
Application of Transfer Learning and Ensemble Learning in Image-level Classification for Breast Histopathology—0
Industrial Federated Learning -- Requirements and System Design—0
Application of Low-resource Machine Translation Techniques to Russian-Tatar Language Pair—0
Industrial Scene Change Detection using Deep Convolutional Neural Networks—0
Inexact-ADMM Based Federated Meta-Learning for Fast and Continual Edge Learning—0
Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies—0
Inference is All You Need: Self Example Retriever for Cross-domain Dialogue State Tracking with ChatGPT—0
Better transfer learning with inferred successor maps—0
Inferring Analogous Attributes—0
Semi-supervised Chinese Word Segmentation for CLP2012—0
GSDA: Generative Adversarial Network-based Semi-Supervised Data Augmentation for Ultrasound Image Classification—0
Terabyte-scale supervised 3D training and benchmarking dataset of the mouse kidney—0
A Comprehensive Survey on Architectural Advances in Deep CNNs: Challenges, Applications, and Emerging Research Directions—0
InfLocNet: Enhanced Lung Infection Localization and Disease Detection from Chest X-Ray Images Using Lightweight Deep Learning—0
Info3D: Representation Learning on 3D Objects using Mutual Information Maximization and Contrastive Learning—0
InFoBERT: Zero-Shot Approach to Natural Language Understanding Using Contextualized Word Embedding—0
VFed-SSD: Towards Practical Vertical Federated Advertising—0
Information-theoretic analysis for transfer learning—0
Information-Theoretic Bounds on Transfer Generalization Gap Based on Jensen-Shannon Divergence—0
Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection—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