Envisioning Navigation: Harnessing AI for Assistive Solutions
Navigating the development of an assistive indoor technology for the visually impaired, my PhD journey intersected with Google's advanced tools. Tasked with optimizing location accuracy on budget smartphones, I integrated methodologies reminiscent of those in autonomous vehicle systems. The application utilized TensorFlow Lite's version of YOLO from GCP for obstacle detection, enhanced with transfer learning to widen object recognition capabilities. Google's text-to-speech and speech recognition APIs became pivotal, filling the gap in my resource constraints. This talk underscores the power of leveraging accessible tools in creating impactful, innovative tech solutions, while offering insights into the practical challenges and successes of my endeavour.
About Roya Kandalan:
Roya is a research scientist who is passionate about advancing artificial intelligence technologies. She is particularly interested in computer vision and pattern recognition and has developed machine learning solutions for a variety of applications, including healthcare, assistive technology, and security.
Roya is also an advocate for women's rights. She is a Google Women's Techmaker Ambassador and a Google Developer Group organizer. She uses these platforms to encourage women to pursue careers in science and technology.
#Google #TensorFlowLite #YOLO #ComputerVision #AssistiveTechnology #VisuallyImpaired #AutonomousVehicles #Texttospeech #SpeechRecognition #Innovation #technology #Diversity #Inclusion #womenintech #googleai
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