"Revolutionizing retail through Automated Self-Checkout using AI vision-based computing"
"Revolutionizing retail through Automated Self-Checkout using AI vision-based computing"
24 - 5:10 PM EDT/New York (See in local time)
Add to Calendar
04/24/2024 5:10 PM
04/24/2024 05:30 PM
America/New_York
#WTGC2024
"Revolutionizing retail through Automated Self-Checkout using AI vision-based computing"
#WTGC2024
"Revolutionizing retail through Automated Self-Checkout using AI vision-based computing"
https://app.events.ringcentral.com/events/women-in-tech-global-conference-2024/reception
https://www.womentech.net/vfairs
"Revolutionizing retail through Automated Self-Checkout using AI vision-based computing"
"Revolutionizing retail through Automated Self-Checkout using AI vision-based computing"
Don’t miss out and join visionaries, innovators, and thought leaders from all over the world at the Women in Tech Global Conference.
Vote by Sharing
Unite 100 000 Women in Tech to Drive Change with Purpose and Impact.
Do you want to see this session? Help increase the sharing count and the session visibility. Sessions with +10 votes will be available to career ticket holders.
Please note that it might take some time until your share & vote is reflected.
Session: Revolutionizing retail through Automated Self-Checkout using AI vision-based computing
Computer vision is revolutionizing various industries, and retail is no exception. While AI applications have many benefits, proof-of-concepts do not scale successfully into larger, implemented deployments. Retailers, independent software vendors (ISVs), and system integrators (SIs) require a good understanding of both hardware and software, maintaining AI models in production and having in-depth knowledge of costs involved in setting up and scaling these systems. Vision workloads are significantly larger, complex, undergo multiple stages of processing and therefore require systems to be architected, built, and deployed with several considerations. To make it easier for software developers to understand the optimizations and hardware capabilities, Automated Self-Checkout is developed- an open-source initiative for vision-enabled retail use cases, providing optimized code blocks, documentation, and performance benchmark data to enhance and accelerate developer’s product and project work. Hence, a set of ingredients are needed to create vision-enabled use cases by adopting the AI Enabled Checkout Framework.Key Takeaways
- Identify the challenges in implementing computer vision-based AI/ML solutions for retail use cases.
- Describe the Automated Self-Checkout reference implementation solution that has revolutionized the retail space.
- Describe the hardware benchmarking feature included in this innovative solution
Bio
Valina Li is a senior software engineer in AI Solutions team of Network & Edge Group at Intel Corporation, with experience in Windows, Android, and Linux software developments. She is interested in software security, holding Intel’s software security silver and gold belt certificates. Lately she has been more involved with microservices development, building smart end-to-end computer vision-based automation solutions in retail and healthcare. Valina holds a Bachelor of Science degree in Computer Science and Engineering from the University of California, Los Angeles. She spoke about “Scalability and Product Focused Design” in Intel’s Software Professionals Conference in 2017. LinkedIn – https://www.linkedin.com/in/valinali/Neethu Elizabeth Simon is an IOT/ML Senior Software Engineer in Network & Edge Group at Intel Corporation, with vast industrial experience in building smart end-to-end computer vision-based Machine Learning solutions in retail, biopharma, healthcare etc. Neethu holds Master’s in Computer Science from Arizona State University and demonstrates her proficiency by presenting at multiple global conferences(e.g. GHC, SWE, Open-Source-Summit) including analytics and software professional conferences and is often invited to share her expertise with college students. She also shares her technical knowledge by leading & reviewing technical conferences, patent filings and book publications. Neethu is recipient of 2023-Women Who Code – Applaud Her Award for achieving excellence, innovation in industry and showing leadership and 2020 Society of Women Engineers Distinguished New Engineer Award for being powerful technical contributor, for encouraging a diverse and inclusive work environment and for being ally for improving diversity through educational outreach.
Apart from her day job, Neethu currently leads the global Technical Women in Intel(TWIN) Cross-site group and has previously led the Intel India-AZ Employee Resource Group (ERG) for several years where in she has organized multiple cultural, networking, STEM volunteering and career development events. Outside work, Neethu is passionate about promoting girls in STEM, women in technology, Diversity and Inclusion(D&I). She is an active member of the IEEE Women in Engineering(WIE), Phoenix section and Society of Women Engineers(SWE), contributing at both society level and with the Phoenix chapter.
