Deep Learning for Vision: Tricks of the Trade
Explore deep learning's evolution in computer vision, from unsupervised algorithms to modern object recognition systems. Learn practical tips and future challenges in this field.
Machine Learning at the Extreme Edge of Always-on Intelligent Sensor Networks
Explore ML optimization techniques for resource-constrained IoT sensor nodes, focusing on system, algorithm, architecture, and circuit levels to achieve significant area-power improvements.
Why It Pays to Study Psychology - Lessons from Computer Vision
Explore how psychology insights enhance computer vision, from texture analysis to scene recognition and 3D reasoning. Learn about occlusion, visual memory, and self-supervised learning.
The Modern Trolley Problem - Responsible AI Principles
Explore ethical challenges in AI-driven vehicles, from decision-making algorithms to object recognition. Delve into Responsible AI Principles and their crucial role in shaping autonomous technology's future.
Deep Learning of Generative Models - 2014
Explore generative models in deep learning with Yoshua Bengio, covering motivations, applications, and fundamental challenges in AI and machine learning.
KI-Basierte Modifikation von Videostreams aus Überwachungskameras
Demonstration der KI-basierten Echtzeitmanipulation von Videostreams aus IP-Kameras, einschließlich Entfernung von Personen und Firmware-Modifikationen. Diskussion über Einschränkungen und Gegenmaßnahmen.
What You Always Wanted to Know About Deep Learning, but Were Afraid to Ask
Demystifying deep learning concepts like back-propagation, gradient descent, and neural networks. Practical guide to training a model for object recognition using TensorFlow and Keras.
ViBand - High-Fidelity Bio-Acoustic Sensing Using Commodity Smartwatch Accelerometers
Innovative smartwatch technology enhances bio-acoustic sensing, enabling gesture recognition, object detection, and body-based data transmission, expanding wearable interaction possibilities.
The Modern Trolley Problem - Responsible AI Principles
Explore ethical challenges in AI-driven vehicles, from object recognition to decision-making algorithms. Delve into responsible AI principles and the importance of intentional, transparent coding in autonomous systems.
IoT - Building Machine Vision System
Explore IoT machine vision systems, from AI-enabled solutions to object recognition, using Windows 10 IoT Core and UWP. Learn about image processing, emotion detection, and custom implementations.
Microsoft Cognitive Services - Making AI Easy
Explore 20+ Cognitive Services APIs for AI-powered applications, including object recognition, speech processing, and language understanding. Learn implementation techniques and gain inspiration for intelligent app development.
Developing Object Recognition for HoloLens
Learn to develop object recognition for HoloLens using Vuforia AR SDK. Explore applications in modern art, asset management, and more in this billion-dollar market.
What's That Fruit
Explore image classification and object detection using Microsoft Cognitive Services, from cloud-based solutions to edge computing, with simplified explanations and practical code examples.
What You Always Wanted to Know About Deep Learning, but Were Afraid to Ask
Demystifying Deep Learning: key concepts, practical applications, and hands-on training for object recognition. Gain a clear understanding of AI fundamentals and start your journey into machine learning.
Intersection over Union (IoU) Explained with PyTorch
Learn to implement Intersection over Union (IoU) for object recognition using PyTorch. Covers theory, formulas, and practical code for bounding boxes and segmentation masks.
Is Machine Learning Smarter Than a Toddler? - Roboflow + OpenCV Webinar
Explore how AI and ML compare to toddlers in object recognition, drawing, and writing. Gain insights into the current capabilities and limitations of machine learning technology.
The Modern Trolley Problem
Exploring ethical dilemmas in self-driving car algorithms, demonstrating object recognition, and discussing responsible AI principles and sustainable engineering practices.
The Modern Trolley Problem - Responsible AI Principles
Exploring ethical challenges in AI-driven vehicles, from object recognition to decision-making algorithms. Demonstrates model training and deployment while emphasizing responsible AI principles and sustainable engineering practices.
Scene Graphs: Overview and Current Research
Explore scene graphs and current research in this field, gaining insights into an exciting area of AI and machine learning.
The Modern Trolley Problem - Responsible AI Principals
Explore ethical challenges in AI-driven vehicles, from blame allocation to algorithm design. Discover object recognition, obstacle avoidance, and responsible AI principles for sustainable engineering practices.
Understanding the Visual World Through Object Intrinsics
Explore neuro-symbolic approaches to scene and object understanding, focusing on intrinsic structures and their role in visual data interpretation and generalization.