1. HiMax: EE396 Biometric With CogniMem Device (Neural Processor)

2. Presentation Overview: Team and Member Introduction Brief Project Overview and Technology Background Approaches – Phase 1 – Phase 2 – Phase 3 Possible Problems (guarantee there will be some!) End of Semester Project Goals Project Timeline Presentation Summary References Q&A session

3. HiMax: EE396 Biometric With CogniMem Device (Neural Processor) Advisor: Dr.Tep Dobry Sub Advisor: Dr. Neil Scott Dr. Winyu Chinthammit Members: Raymundo Flores James Cuaresma

4. Team and Member Introduction: HiMax Group: Archimedes Project - UH – Develop and research “enabling technologies”. – Dr. Neil Scott - Founder Communication and Information Sciences - UH Manoa – Laboratory for Interactive Learning Technologies – Dr. Winyu Chinthammit - Junior Researcher Electrical Engineering - UH Manoa - Raymundo Flores & James Cuaresma (da Undergrads!)

5. Project Overview: This technology is fairly new, so we propose: 1. Research methodology for an “efficient training” of the CogniMem Neural processor. 2. Develop “reproducible procedures” for a "high-level confidence" for “Facial Biometric recognition” application in a static physical environment. 3. As needed, create hardware interface with the device; develop software for a particular application.

6. Project Background: CogniMem 1K Specs - Patented parallel architecture - 1024 Parallel neurons - Unlimited neural network expansion - Trained by example - Low power consumption Image Recognition Board www.recognetics.com

7. Background: CogniMem Device Diagram

8. Approaches: Phase 1  Create a “controlled environment” to characterize the Biometric limits of the CogniMem device with respect to known environmental changes (more elaboration is just a sec). Phase 2  With lesson learned in Phase 1: Will implement a controlled-group “open environment” characterization/testing of the device (more elaboration is just a sec). Phase 3  Verification and “variable-environment” testing of the controlled- group (8 individuals) to the general population  False-Positive  Control group (thru external facial manipulation) to deceive & create “Positive  Unknown” identification

9. Phase 1: Controlled Environment Diagram

10. Phase 2: Controlled-Group (Open- Environment) To Be Determined

11. Phase 3: Verification – Testing (Variable- Environment) To Be Determined

12. Problems: Hardware and software has only been recently developed and product knowledge is still limited at this time. – Manufacturer / vendor technical support are via e-mails and voicemails. There will be ‘delays’ in resolving certain issues and problems. – Internet ‘information mining’ is required. Hardware is very expensive and reacquiring a new integrated chip and camera may take a long time. – Device is $900.00 – Take special care of equipment. – Loan while ‘in-repair’ policy: none. Just have to wait until your particular device is fixed. There is a long repair cycle! – Backup Device

13. End of Semester Project Goals: Our projected goals are to: Develop efficient training methodology of the CogniMem device. Develop “reproducible procedures” for a "high-level confidence" Biometric recognition training. Have a working model for a static Facial Biometric identification that is reliable. EE496: Lay the ground-work for a “dynamic” Facial/Body Biometric follow-on project.

14. Project Timeline 9/15-9/269/27-10/1010/11-10/2410/25-11/711/8-11/2111/22-12/512/6-12/12 Presentations Proposal PDR CDR Final Tasks Obtain Lab Set up Lab Familiarize with Cognimem (James) Paliminary testing Training on volunteers Known to unknown ratio testing

15. Presentation Summary: Key Technology: CogniMem Neural Processor (1024 parallel neurons) Method of Modeling: Learn and build knowledge by example vectors (i.e. camera, microphone). No cumbersome programming required. Challenges: Fairly new technology Minimal data/information available Lay "ground" work for future applications Main System Diagrams: Controlled Environment CogniMem Device

16. References: 1. http://wiki.roadnarrows.com - Distributor 2. http://www.general-vision.com - Researchers 3. http://www.recognetics.com - Developers

17. ?Any Questions?