Главная
Study mode:
on
1
Introduction
2
Introducing the speaker
3
What is tinyML
4
Background
5
Use Cases
6
Traditional Approaches
7
Adaptive Compute
8
Human Detection
9
Person Detection
10
Gesture Detection
11
Lighting
12
Phase Detection
13
Image Examples
14
Latency Requirements
15
Demo
16
ML Tools
17
Tuner
18
AI Engine
19
QA
20
Conclusion
Description:
Explore the cutting-edge developments in ultra-low power always-on computer vision at Qualcomm in this tinyML Talks Morocco presentation. Delve into the challenges of achieving computer vision at 1mW for TinyML applications and discover the innovative solutions across sensor technology, custom ASIC components, architecture, algorithms, software, and trainable models. Learn about Qualcomm Technologies' always-on computer vision module, featuring a low-power monochrome qVGA CMOS image sensor and an ultra-low power custom SoC. Understand how challenging traditional computer vision assumptions is enabling new applications in mobile phones, wearables, and IoT. Gain insights into the Qualcomm QCC112 chip, its potential use cases, and the overview of training tools for always-on computer vision systems. Follow the presentation's structure, covering topics such as tinyML background, use cases, adaptive compute, human and person detection, gesture recognition, lighting considerations, and ML tools like Tuner and AI Engine. Read more

TinyML Talks Morocco - Enabling Ultra-Low Power Always-On Computer Vision at Qualcomm

tinyML
Add to list