Picture for Jingtao Li

Jingtao Li

Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization

Apr 02, 2024
Figure 1 for Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization
Figure 2 for Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization
Figure 3 for Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization
Figure 4 for Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization
Viaarxiv icon

A Unified Remote Sensing Anomaly Detector Across Modalities and Scenes via Deviation Relationship Learning

Add code
Oct 11, 2023
Figure 1 for A Unified Remote Sensing Anomaly Detector Across Modalities and Scenes via Deviation Relationship Learning
Figure 2 for A Unified Remote Sensing Anomaly Detector Across Modalities and Scenes via Deviation Relationship Learning
Figure 3 for A Unified Remote Sensing Anomaly Detector Across Modalities and Scenes via Deviation Relationship Learning
Figure 4 for A Unified Remote Sensing Anomaly Detector Across Modalities and Scenes via Deviation Relationship Learning
Viaarxiv icon

Class Prior-Free Positive-Unlabeled Learning with Taylor Variational Loss for Hyperspectral Remote Sensing Imagery

Add code
Aug 29, 2023
Figure 1 for Class Prior-Free Positive-Unlabeled Learning with Taylor Variational Loss for Hyperspectral Remote Sensing Imagery
Figure 2 for Class Prior-Free Positive-Unlabeled Learning with Taylor Variational Loss for Hyperspectral Remote Sensing Imagery
Figure 3 for Class Prior-Free Positive-Unlabeled Learning with Taylor Variational Loss for Hyperspectral Remote Sensing Imagery
Figure 4 for Class Prior-Free Positive-Unlabeled Learning with Taylor Variational Loss for Hyperspectral Remote Sensing Imagery
Viaarxiv icon

One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning

Mar 22, 2023
Figure 1 for One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning
Figure 2 for One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning
Figure 3 for One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning
Figure 4 for One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning
Viaarxiv icon

Model Extraction Attacks on Split Federated Learning

Mar 13, 2023
Figure 1 for Model Extraction Attacks on Split Federated Learning
Figure 2 for Model Extraction Attacks on Split Federated Learning
Figure 3 for Model Extraction Attacks on Split Federated Learning
Figure 4 for Model Extraction Attacks on Split Federated Learning
Viaarxiv icon

Anomaly Segmentation for High-Resolution Remote Sensing Images Based on Pixel Descriptors

Add code
Jan 31, 2023
Figure 1 for Anomaly Segmentation for High-Resolution Remote Sensing Images Based on Pixel Descriptors
Figure 2 for Anomaly Segmentation for High-Resolution Remote Sensing Images Based on Pixel Descriptors
Figure 3 for Anomaly Segmentation for High-Resolution Remote Sensing Images Based on Pixel Descriptors
Figure 4 for Anomaly Segmentation for High-Resolution Remote Sensing Images Based on Pixel Descriptors
Viaarxiv icon

Split Federated Learning on Micro-controllers: A Keyword Spotting Showcase

Oct 04, 2022
Figure 1 for Split Federated Learning on Micro-controllers: A Keyword Spotting Showcase
Figure 2 for Split Federated Learning on Micro-controllers: A Keyword Spotting Showcase
Figure 3 for Split Federated Learning on Micro-controllers: A Keyword Spotting Showcase
Figure 4 for Split Federated Learning on Micro-controllers: A Keyword Spotting Showcase
Viaarxiv icon

An Adjustable Farthest Point Sampling Method for Approximately-sorted Point Cloud Data

Add code
Aug 18, 2022
Figure 1 for An Adjustable Farthest Point Sampling Method for Approximately-sorted Point Cloud Data
Figure 2 for An Adjustable Farthest Point Sampling Method for Approximately-sorted Point Cloud Data
Figure 3 for An Adjustable Farthest Point Sampling Method for Approximately-sorted Point Cloud Data
Figure 4 for An Adjustable Farthest Point Sampling Method for Approximately-sorted Point Cloud Data
Viaarxiv icon

ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning

Add code
May 09, 2022
Figure 1 for ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning
Figure 2 for ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning
Figure 3 for ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning
Figure 4 for ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning
Viaarxiv icon

Communication and Computation Reduction for Split Learning using Asynchronous Training

Jul 20, 2021
Figure 1 for Communication and Computation Reduction for Split Learning using Asynchronous Training
Figure 2 for Communication and Computation Reduction for Split Learning using Asynchronous Training
Figure 3 for Communication and Computation Reduction for Split Learning using Asynchronous Training
Figure 4 for Communication and Computation Reduction for Split Learning using Asynchronous Training
Viaarxiv icon