NSF PAR Search | NSF Public Access Repository

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

Bimodal Profile Diagrams for Breast Cancer Classification Using Convolution Neural Network

https://doi.org/10.1109/JSEN.2025.3533385

Rahman, Nazia; Oleksyuk, Vira; Won, Chang-Hee (March 2025, IEEE Sensors Journal)

Free, publicly-accessible full text available March 15, 2026
Dynamic Sensing of an Embedded Object Using Laser, Camera, and Collaborative Robot

https://doi.org/10.1109/SENSORS60989.2024.10784867

Bannan, John; Rahman, Nazia; Won, Chang-Hee (October 2024, IEEE)

Full Text Available
Tactile Sensing System and Convolutional Neural Network for Mechanical Property Classification

https://doi.org/10.1109/LSENS.2023.3310356

Oleksyuk, Vira; Rahman, Nazia; Won, Chang-Hee (October 2023, IEEE Sensors Letters)

Full Text Available
Identifying Benign and Malignant Breast Tumor Using Vibro-acoustic Tactile Imaging Sensor

https://doi.org/10.1109/SENSORS52175.2022.9967083

Rahman, Nazia; Won, Chang-hee (October 2022, IEEE Sensors Conference)

Tactile imaging sensor determines the tumor's mechanical properties such as size, depth, and Young's modulus based on the principle of total internal reflection of light. To improve the classifying accuracy of the Tactile imaging sensor, we introduce ultrasound signals and estimate the difference in the tumor tactile images. A developed vibro-acoustic tactile imaging sensor was used to classify benign and malignant tumors. We test the developed system on breast tumor phantoms. These vibrated tactile images are analyzed to improve the overall performance of tumor detection.
more » « less
Full Text Available

Search for: All records