Patents by Inventor Weicong SNG

Weicong SNG has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • EVENT-DRIVEN VISUAL-TACTILE SENSING AND LEARNING FOR ROBOTS
    Publication number: 20250214255
    Abstract: A classifying sensing system, a classifying method performed using a sensing system, a tactile sensor, and a method of fabricating a tactile sensor. The classifying sensing system comprises a first spiking neural network, SNN, encoder configured for encoding an event-based output of a vision sensor into individual vision modality spiking representations with a first output size; a second SNN encoder configured for encoding an event-based output of a tactile sensor into individual tactile modality spiking representations with a second output size; a combination layer configured for merging the vision modality spiking representations and the tactile modality spiking representations; and a task SNN configured to receive the merged vision modality spiking representations and tactile modality spiking representations and output vision-tactile modality spiking representations with a third output size for classification.
    Type: Application
    Filed: February 21, 2025
    Publication date: July 3, 2025
    Applicant: NATIONAL UNIVERSITY OF SINGAPORE
    Inventors: Chee Keong TEE, Hian Hian SEE, Brian LIM, Soon Hong Harold SOH, Tasbolat TAUNYAZOV, Weicong SNG, Sheng Yuan Jethro KUAN, Abdul Fatir ANSARI
  • Event-driven visual-tactile sensing and learning for robots
    Patent number: 12257727
    Abstract: A classifying sensing system, a classifying method performed using a sensing system, a tactile sensor, and a method of fabricating a tactile sensor. The classifying sensing system comprises a first spiking neural network, SNN, encoder configured for encoding an event-based output of a vision sensor into individual vision modality spiking representations with a first output size; a second SNN encoder configured for encoding an event-based output of a tactile sensor into individual tactile modality spiking representations with a second output size; a combination layer configured for merging the vision modality spiking representations and the tactile modality spiking representations; and a task SNN configured to receive the merged vision modality spiking representations and tactile modality spiking representations and output vision-tactile modality spiking representations with a third output size for classification.
    Type: Grant
    Filed: June 15, 2021
    Date of Patent: March 25, 2025
    Assignee: NATIONAL UNIVERSITY OF SINGAPORE
    Inventors: Chee Keong Tee, Hian Hian See, Brian Lim, Soon Hong Harold Soh, Tasbolat Taunyazov, Weicong Sng, Sheng Yuan Jethro Kuan, Abdul Fatir Ansari
  • EVENT-DRIVEN VISUAL-TACTILE SENSING AND LEARNING FOR ROBOTS
    Publication number: 20230330859
    Abstract: A classifying sensing system, a classifying method performed using a sensing system, a tactile sensor, and a method of fabricating a tactile sensor. The classifying sensing system comprises a first spiking neural network, SNN, encoder configured for encoding an event-based output of a vision sensor into individual vision modality spiking representations with a first output size; a second SNN encoder configured for encoding an event-based output of a tactile sensor into individual tactile modality spiking representations with a second output size; a combination layer configured for merging the vision modality spiking representations and the tactile modality spiking representations; and a task SNN configured to receive the merged vision modality spiking representations and tactile modality spiking representations and output vision-tactile modality spiking representations with a third output size for classification.
    Type: Application
    Filed: June 15, 2021
    Publication date: October 19, 2023
    Applicant: NATIONAL UNIVERSITY OF SINGAPORE
    Inventors: Chee Keong TEE, Hian Hian SEE, Brian LIM, Soon Hong Harold SOH, Tasbolat TAUNYAZOV, Weicong SNG, Sheng Yuan Jethro KUAN, Abdul Fatir ANSARI