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
Vector representations of text data in deep learning—0
Vehicle Detection of Multi-source Remote Sensing Data Using Active Fine-tuning Network—0
Vehicle Detection Performance in Nordic Region—0
Vehicle Trajectory Prediction by Transfer Learning of Semi-Supervised Models—0
Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation—0
Versatile and Robust Transient Stability Assessment via Instance Transfer Learning—0
Vertical Federated Knowledge Transfer via Representation Distillation for Healthcare Collaboration Networks—0
VGSG: Vision-Guided Semantic-Group Network for Text-based Person Search—0
Vicinal Risk Minimization for Few-Shot Cross-lingual Transfer in Abusive Language Detection—0
VideoAdviser: Video Knowledge Distillation for Multimodal Transfer Learning—0
Video and Synthetic MRI Pre-training of 3D Vision Architectures for Neuroimage Analysis—0
Video Anomaly Detection using GAN—0
Video-based Pose-Estimation Data as Source for Transfer Learning in Human Activity Recognition—0
Video Contents Understanding using Deep Neural Networks—0
Unboxing Engagement in YouTube Influencer Videos: An Attention-Based Approach—0
Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video Action Recognition—0
Video Surveillance of Highway Traffic Events by Deep Learning Architectures—0
VieSum: How Robust Are Transformer-based Models on Vietnamese Summarization?—0
Viewing Knowledge Transfer in Multilingual Machine Translation Through a Representational Lens—0
Viewpoint Invariant Action Recognition using RGB-D Videos—0
VIPriors 2: Visual Inductive Priors for Data-Efficient Deep Learning Challenges—0
VIPriors 3: Visual Inductive Priors for Data-Efficient Deep Learning Challenges—0
VIPriors 4: Visual Inductive Priors for Data-Efficient Deep Learning Challenges—0
Virtual Battery Parameter Identification using Transfer Learning based Stacked Autoencoder—0
Virtual-to-Real-World Transfer Learning for Robots on Wilderness Trails—0
Vision-Based Layout Detection from Scientific Literature using Recurrent Convolutional Neural Networks—0
Vision Based Machine Learning Algorithms for Out-of-Distribution Generalisation—0
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
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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