"SoCs for Computer Vision-enabled IoT Devices," a March 2019 Silicon Valley Meetup Presentation from MediaTek
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The document discusses MediaTek's NeuroPilot platform and tools for AI and machine learning. It describes several MediaTek AI hardware and software technologies, including a platform-aware ML kit with network reduction, architecture search, and deep fusion capabilities. It also outlines NeuroPilot tools for developers, including integration with Android Neural Networks, support for frameworks like TensorFlow and Caffe, and utilities for quantization, profiling, and debugging.
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For the full video of this presentation, please visit:
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For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/sept-2018-alliance-vitf-khronos
For more information about embedded vision, please visit:
http://www.embedded-vision.com
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For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2020/11/deploying-deep-learning-applications-on-fpgas-with-matlab-a-presentation-from-mathworks/
For more information about edge AI and computer vision, please visit:
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For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2020/11/deploying-deep-learning-applications-on-fpgas-with-matlab-a-presentation-from-mathworks/
For more information about edge AI and computer vision, please visit:
https://www.edge-ai-vision.com
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For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/sep-2019-alliance-vitf-cocoonhealth
For more information about embedded vision, please visit:
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For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/computer-vision-in-sports-scalable-solutions-for-downmarkets-a-presentation-from-sportlogiq/
Mehrsan Javan, Co-founder and CTO of Sportlogiq, presents the “Computer Vision in Sports: Scalable Solutions for Downmarket Leagues” tutorial at the May 2023 Embedded Vision Summit.
Sports analytics is about observing, understanding and describing the game in an intelligent manner. In practice, this requires a fully automated, robust end-to-end pipeline, spanning from visual input, to player and group activities, to player and team evaluation to planning. Despite major advancements in computer vision and machine learning, today sports analytics solutions are limited to top leagues and are not widely available for downmarket leagues and youth sports.
In this talk, Javan explains how his company has developed scalable and robust computer vision solutions to democratize sport analytics and offer pro-league-level insights to leagues with modest resources, including youth leagues. He highlights key challenges—such as the requirement for low-cost, low-latency processing and the need for robustness despite variations in venues. He discusses the approaches Sportlogiq tried and how it ultimately overcame these challenges, including the use of transformers and fusion of multiple type of data streams to maximize accuracy.“Computer Vision in Sports: Scalable Solutions for Downmarkets,” a Presentati...
“Computer Vision in Sports: Scalable Solutions for Downmarkets,” a Presentati...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/detecting-data-drift-in-image-classification-neural-networks-a-presentation-from-southern-illinois-university/
Spyros Tragoudas, Professor and School Director at Southern Illinois University Carbondale, presents the “Detecting Data Drift in Image Classification Neural Networks” tutorial at the May 2023 Embedded Vision Summit.
An unforeseen change in the input data is called “drift,” and may impact the accuracy of machine learning models. In this talk, Tragoudas presents a novel scheme for diagnosing data drift in the input streams of image classification neural networks. His proposed method for drift detection and quantification uses a threshold dictionary for the prediction probabilities of each class in the neural network model.
The method is applicable to any drift type in images such as noise and weather effects, among others. Tragoudas shares experimental results on various data sets, drift types and neural network models to show that his proposed method estimates the drift magnitude with high accuracy, especially when the level of drift significantly impacts the model’s performance.“Detecting Data Drift in Image Classification Neural Networks,” a Presentatio...
“Detecting Data Drift in Image Classification Neural Networks,” a Presentatio...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/deep-neural-network-training-diagnosing-problems-and-implementing-solutions-a-presentation-from-sensor-cortek/
Fahed Hassanat, Chief Operating Officer and Head of Engineering at Sensor Cortek, presents the “Deep Neural Network Training: Diagnosing Problems and Implementing Solutions” tutorial at the May 2023 Embedded Vision Summit.
In this presentation, Hassanat delves into some of the most common problems that arise when training deep neural networks. He provides a brief overview of essential training metrics, including accuracy, precision, false positives, false negatives and F1 score.
Hassanat then explores training challenges that arise from problems with hyperparameters, inappropriately sized models, inadequate models, poor-quality datasets, imbalances within training datasets and mismatches between training and testing datasets. To help detect and diagnose training problems, he also covers techniques such as understanding performance curves, recognizing overfitting and underfitting, analyzing confusion matrices and identifying class interaction issues.
“Deep Neural Network Training: Diagnosing Problems and Implementing Solutions...
“Deep Neural Network Training: Diagnosing Problems and Implementing Solutions...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/ai-start-ups-the-perils-of-fishing-for-whales-war-stories-from-the-entrepreneurial-front-lines-a-presentation-from-seechange-technologies/
Tim Hartley, Vice President of Product for SeeChange Technologies, presents the “AI Start-ups: The Perils of Fishing for Whales (War Stories from the Entrepreneurial Front Lines)” tutorial at the May 2023 Embedded Vision Summit.
You have a killer idea that will change the world. You’ve thought through product-market fit and differentiation. You have seed funding and a world-beating team. Best of all, you’ve caught the attention of major players in your industry. You’ve reached peak “start-up”—that point of limitless possibility—when you go to bed with the same level of energy and enthusiasm you had when you woke. And then the first proof of concept starts…
In this talk, Hartley lays out some of the pitfalls that await those building the next big thing. Using real examples, he shares some of the dos and don’ts, particularly when dealing with that big potential first customer. Hartley discusses the importance of end-to-end design, ensuring your product solves real-world problems. He explores how far the big companies will tell you to jump—and then jump again—for free. And, most importantly, how to build long-term partnerships with major corporations without relying on over-promising sales pitches.“AI Start-ups: The Perils of Fishing for Whales (War Stories from the Entrepr...
“AI Start-ups: The Perils of Fishing for Whales (War Stories from the Entrepr...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/a-computer-vision-system-for-autonomous-satellite-maneuvering-a-presentation-from-scout-space/
Andrew Harris, Spacecraft Systems Engineer at SCOUT Space, presents the “Developing a Computer Vision System for Autonomous Satellite Maneuvering” tutorial at the May 2023 Embedded Vision Summit.
Computer vision systems for mobile autonomous machines experience a wide variety of real-world conditions and inputs that can be challenging to capture accurately in training datasets. Few autonomous systems experience more challenging conditions than those in orbit. In this talk, Harris describes how SCOUT Space has designed and trained satellite vision systems using dynamic and physically informed synthetic image datasets.
Harris describes how his company generates synthetic data for this challenging environment and how it leverages new real-world data to improve our datasets. In particular, he explains how these synthetic datasets account for and can replicate real sources of noise and error in the orbital environment, and how his company supplements them with in-space data from the first SCOUT-Vision system, which has been in orbit since 2021.“A Computer Vision System for Autonomous Satellite Maneuvering,” a Presentati...
“A Computer Vision System for Autonomous Satellite Maneuvering,” a Presentati...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/bias-in-computer-vision-its-bigger-than-facial-recognition-a-presentation-from-santa-clara-university/
Susan Kennedy, Assistant Professor of Philosophy at Santa Clara University, presents the “Bias in Computer Vision—It’s Bigger Than Facial Recognition!” tutorial at the May 2023 Embedded Vision Summit.
As AI is increasingly integrated into various industries, concerns about its potential to reproduce or exacerbate bias have become widespread. While the use of AI holds the promise of reducing bias, it can also have unintended consequences, particularly in high-stakes computer vision applications such as facial recognition. However, even seemingly low-stakes computer vision applications such as identifying potholes and damaged roads can also present ethical challenges related to bias.
This talk explores how bias in computer vision often poses an ethical challenge, regardless of the stakes involved. Kennedy discusses the limitations of technical solutions aimed at mitigating bias, and why “bias-free” AI may not be achievable. Instead, she focuses on the importance of adopting a “bias-aware” approach to responsible AI design and explores strategies that can be employed to achieve this.“Bias in Computer Vision—It’s Bigger Than Facial Recognition!,” a Presentatio...
“Bias in Computer Vision—It’s Bigger Than Facial Recognition!,” a Presentatio...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/sensor-fusion-techniques-for-accurate-perception-of-objects-in-the-environment-a-presentation-from-sanborn-map-company/
Baharak Soltanian, Vice President of Research and Development for the Sanborn Map Company, presents the “Sensor Fusion Techniques for Accurate Perception of Objects in the Environment” tutorial at the May 2023 Embedded Vision Summit.
Increasingly, perceptual AI is being used to enable devices and systems to obtain accurate estimates of object locations, speeds and trajectories. In demanding applications, this is often best done using a heterogeneous combination of sensors (e.g., vision, radar, LiDAR). In this talk, Soltanian introduces techniques for combining data from multiple sensors to obtain accurate information about objects in the environment.
Soltanian briefly introduces the roles played by Kalman filters, particle filters, Bayesian networks and neural networks in this type of fusion. She then examines alternative fusion architectures, such as centralized and decentralized approaches, to better understand the trade-offs associated with different approaches to sensor fusion as used to enhance the ability of machines to understand their environment.“Sensor Fusion Techniques for Accurate Perception of Objects in the Environme...
“Sensor Fusion Techniques for Accurate Perception of Objects in the Environme...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/combating-bias-in-production-computer-vision-systems-a-presentation-from-red-cell-partners/
Alex Thaman, Chief Architect at Red Cell Partners, presents the “Combating Bias in Production Computer Vision Systems” tutorial at the May 2023 Embedded Vision Summit.
Bias is a critical challenge in predictive and generative AI that involves images of humans. People have a variety of body shapes, skin tones and other features that can be challenging to represent completely in training data. Without attention to bias risks, ML systems have the potential to treat people unfairly, and even to make humans more likely to do so.
In this talk, Thaman examines the ways in which bias can arise in visual AI systems. He shares techniques for detecting bias and strategies for minimizing it in production AI systems.“Combating Bias in Production Computer Vision Systems,” a Presentation from R...
“Combating Bias in Production Computer Vision Systems,” a Presentation from R...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/developing-an-embedded-vision-ai-powered-fitness-system-a-presentation-from-peloton-interactive/
Sanjay Nichani, Vice President for Artificial Intelligence and Computer Vision at Peloton Interactive, presents the “Developing an Embedded Vision AI-powered Fitness System” tutorial at the May 2023 Embedded Vision Summit.
The Guide is Peloton’s first strength-training product that runs on a physical device and also the first that uses AI technology. It turns any TV into an interactive personal training studio. Members have access to Peloton’s instructors, who lead classes that use dumbbells and body weight. The Guide uses an innovative combination of hardware, software and user interface; it is one of only a handful of consumer products in this market that use real-time embedded computer vision, and Peloton’s members love it!
In this talk, Nichani shares insights into how the computer vision technology behind the Guide was built. He focuses on data, models and processes. The AI and Computer Vision team at Peloton worked through numerous obstacles by using synthetic data, advanced algorithms and field-testing iteration to create an affordable AI-powered device that enables at-home fitness for everyone.“Developing an Embedded Vision AI-powered Fitness System,” a Presentation fro...
“Developing an Embedded Vision AI-powered Fitness System,” a Presentation fro...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/navigating-the-evolving-venture-capital-landscape-for-edge-ai-start-ups-a-presentation-from-hpe-pathfinder/
Todd Poole, Director of Venture Capital Investments for HPE Pathfinder Ventures, presents the “Navigating the Evolving Venture Capital Landscape for Edge AI Start-ups” tutorial at the May 2023 Embedded Vision Summit.
The venture capital environment has undergone a huge shift in the past year. In this talk, Poole explains how the VC landscape has changed and the implications for start-ups. He examines the impacts on valuations, VC’s willingness to fund, appetite for risk and leverage in deal structuring and terms negotiation.
Pool explores how AI and ML hardware and software companies have been affected differently from the broader start-up ecosystem and considers the distinct challenges faced by start-ups in the edge AI sector. He offers guidance for founders, soon-to-be-founders and start-up employees on how to navigate this dynamic environment and strategize effectively in response to changing market conditions.“Navigating the Evolving Venture Capital Landscape for Edge AI Start-ups,” a ...
“Navigating the Evolving Venture Capital Landscape for Edge AI Start-ups,” a ...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/10/advanced-presence-sensing-what-it-means-for-the-smart-home-a-presentation-from-omdia/
Jack Narcotta, Principal Analyst for the Smart Home at Omdia, presents the “Advanced Presence Sensing: What It Means for the Smart Home” tutorial at the May 2023 Embedded Vision Summit.
Eventually, homes will become highly autonomous—powered by ubiquitous, connected, intelligent devices (sometimes referred to as ambient computing)—but this remains a distant vision. In the meantime, advanced presence sensing innovations from component manufacturers, software developers and smart home device companies are enabling meaningful improvements in convenience, efficiency and safety.
Omdia expects advanced presence detection to be adopted rapidly in the coming years, and to become a key factor in how consumers select devices and service providers. In this talk, Narcotta provides an overview of key enabling technologies, market appetite, consumer expectations and long-term outlook for advanced presence sensing in the home.“Advanced Presence Sensing: What It Means for the Smart Home,” a Presentation...
“Advanced Presence Sensing: What It Means for the Smart Home,” a Presentation...Edge AI and Vision Alliance
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- 1. CONFIDENTIAL A 3/13/2019 Embedded Vision Alliance AIsoftware toolchain andAIA 1
- 2. 2018 Copyright © MediaTek Inc. All rights reserved. 2 NeuroPilot& Platform-awareMLKits
- 3. CONFIDENTIAL A NeuroPilotPlatform-awareMLKits Super-Resolution Depth Estimation Segmentation MediaTek Platform Network Reduction Network Architecture Search Network Deep Fusion (Tiling + Fusion) BW Req.: 2.0GB/s HW Util.: 80% FPS: 100 FPS Power: < 40mW MediaTek Platform-aware MLKits Platform-friendly NN StructureUser-defined NN Structure Application Developers Network Quantization
- 4. 2018 Copyright © MediaTek Inc. All rights reserved. 4 NeuroPilot for Developer • Highly integrated with Android Neural Network • Support Tensorflow as well as Caffe and ONNX • Add useful tools/utilities for developer ANN Runtime ANN API ANN HAL Interpreter .tflite format Tensowflow Model CPU NN HAL impl. GPU NN HAL impl. VPU NN HAL impl. Caffe / ONNX Model MTK Ext. API 1. Bind Op with HW 2.Profiler 3.Debugger (Log) TOCO Model Convertor Offline Tool Quantization NeuroPilot specified On Device CPU GPU VPU Developers AIA NN HAL impl. AIA
- 5. 2018 Copyright © MediaTek Inc. All rights reserved. 5 MediaTek NeuroPilot Toolkit- utility and debug tool NN Utility Debugger Profiling NeuroPilot Toolkit • Model Convertor (TensorFlow/Caffe/ONNX) • Quantization • Power API • Performance • Memory • System Crash • Mobilelog
- 6. 2018 Copyright © MediaTek Inc. All rights reserved. AIA - AI HW Accelerator 6
- 7. 2018 Copyright © MediaTek Inc. All rights reserved. AIA Key Features ▪ Bandwidth reduction techniques - Tile-base layer fusion - TCM for data-exchange - Sparsity compression ▪ Performance Engine MDLA: 806GMAC/s @788MHz ▪ Flexible quantization scheme - Asymmetric or symmetric quant. - Per-layer or per channel quant. - No extra performance overhead ▪ Power Efficient >1 TMACs/W (2x better than VPU) @12FFC ▪ Bandwidth-Aware Design ▪ Dual AXI Port for high BW ▪ High Throughput Load/Store ▪ Simultaneous execution of OPs (CONV/ACT/POOL) ▪ Support INT8/INT16 or FP16
- 8. Copyright © MediaTek Inc. All rights reserved. 8