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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 7976–8000 of 10307 papers

TitleStatusHype
Vision-based Navigation of Autonomous Vehicle in Roadway Environments with Unexpected Hazards—0
Vision-Based Power Line Cables and Pylons Detection for Low Flying Aircraft—0
Vision Based Railway Track Monitoring using Deep Learning—0
Vision Language Transformers: A Survey—0
Vision Learners Meet Web Image-Text Pairs—0
Visual aesthetic analysis using deep neural network: model and techniques to increase accuracy without transfer learning—0
Visual Analogies between Atari Games for Studying Transfer Learning in RL—0
Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection—0
Visual Classifier Prediction by Distributional Semantic Embedding of Text Descriptions—0
Visual DNA: Representing and Comparing Images using Distributions of Neuron Activations—0
Visual Domain Adaptation with Manifold Embedded Distribution Alignment—0
Visual Feature Encoding for GNNs on Road Networks—0
Visual Interest Prediction with Attentive Multi-Task Transfer Learning—0
Visualization of Deep Transfer Learning In SAR Imagery—0
Visualizing Transfer Learning—0
Learning Predicates as Functions to Enable Few-shot Scene Graph Prediction—0
Visual Sentiment Prediction with Deep Convolutional Neural Networks—0
Visuo-Haptic Object Perception for Robots: An Overview—0
ViTaPEs: Visuotactile Position Encodings for Cross-Modal Alignment in Multimodal Transformers—0
ViTOR: Learning to Rank Webpages Based on Visual Features—0
VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks—0
VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for Vietnamese Natural Language Understanding—0
VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understanding—0
Vocabulary Transfer for Biomedical Texts: Add Tokens if You Can Not Add Data—0
Voice Aging with Audio-Visual Style Transfer—0
Show:102550
← PrevPage 320 of 413Next →
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