YOLOv8 Object Detection - First Look Live Coding
Explore YOLOv8 for object detection in Python, from installation to implementation on images, webcams, and videos. Includes hands-on coding and practical demonstrations.
Video Data Processing with Python and OpenCV
Learn to process video data using Python and OpenCV, covering reading, writing, metadata extraction, image manipulation, and annotation. Gain essential skills for machine learning applications in computer vision.
Accelerate Image Annotation with SAM and Grounding DINO - Python Tutorial
Learn to accelerate image annotation using Grounding DINO and Segment Anything Model (SAM). Convert object detection datasets to instance segmentation and explore automatic annotation for real-time detectors like YOLOv8.
Perception and Learning for Autonomous Driving - Part 1
Explore perception and learning for autonomous driving, covering sensor suites, deep neural networks, and object detection techniques in this comprehensive tutorial.
Detecting Masked Faces in the Pandemic World
Explore deep learning techniques for detecting masked faces during the pandemic with Vladimir Iglovikov, a Sr. Computer Vision Engineer at Lyft and Kaggle Grandmaster.
Deja Vu - The Story of Vision & AI
Explore the evolution of computer vision and AI with Ali Farhadi, covering deep neural networks, object detection, visual reasoning, and future predictions in this insightful seminar.
Analysis of Large-Scale Visual Recognition - Bay Area Vision Meeting
Explore large-scale visual recognition challenges, focusing on IMAGENET competitions, object classification, localization techniques, and advancements in computer vision for diverse object classes.
Pixy2 Camera - Image Recognition for Arduino & Raspberry Pi
Explore Pixy2, a smart camera for Arduino and Raspberry Pi projects. Learn setup, training, and coding for object detection, line tracking, and barcode reading.
EON Tuner - AutoML for Constrained Devices in TinyML
Explore AutoML for constrained devices with EON Tuner, optimizing tinyML models through pre-processing, DSP, and ML combinations while considering device limitations and real-world performance.
Streamline Deep Learning for Video Analytics with DeepStream SDK 2.0
Explore AI-based video analytics using DeepStream SDK 2.0 for Tesla, transforming video into insights for smart cities with a modular plugin architecture and scalable framework for multi-stream processing and application development.
Inference and Quantization for AI - Session 3
Explore quantized inference, TensorRT 5, and TensorFlow integration for AI model optimization. Learn about NVIDIA's inference server and techniques to improve model efficiency and performance.
TinyM2Net: A Flexible System Algorithm Co-designed Multimodal Learning Framework for Tiny Devices
Explore a flexible multimodal learning framework for tiny devices, featuring depth separable layers and mixed precision quantization, with applications in COVID detection and object recognition.
EfficientDet - Scalable and Efficient Object Detection
Explore EfficientDet, a scalable object detection model that improves accuracy and efficiency through innovative techniques like BiFPN and compound scaling.
Face Detection with OpenCV
Learn face detection using OpenCV and Python on Raspberry Pi Zero. Explore object detection, AI, neural networks, and computer vision fundamentals. Practical implementation and insights provided.
Adaptive Neural Networks for Agile TinyML - Keynote
Explore adaptive neural networks for efficient tinyML, enabling dynamic footprint minimization and runtime flexibility. Learn about throttleable networks, controller training, and hardware acceleration.
TinyML Vision Challenge - Summit 2021
Discover the tinyML Vision Challenge: Create innovative computer vision applications using tinyML, compete for $6k in prizes, and gain recognition from the tinyML Foundation.
De-risking Embedded Machine Learning Projects Using Novel Technologies
Explore novel technologies for successful embedded machine learning projects, addressing challenges and ensuring customer success through innovative design and engineering philosophies.
TinyML Talks Morocco - Enabling Ultra-Low Power Always-On Computer Vision at Qualcomm
Exploring ultra-low power computer vision for TinyML applications, focusing on Qualcomm's innovations in sensors, hardware, and algorithms to enable always-on vision at 1mW power consumption.
Convolutional Neural Networks
Explore convolutional neural networks for computer vision, covering feature extraction, convolution operations, and applications like object detection and self-driving cars.
Tracking Techniques in Computer Vision - Session 25
Explore advanced tracking techniques and algorithms for object detection and motion analysis in computer vision applications.
Navigating Vision Systems with Weights & Biases and SmartCow
Explore computer vision advancements with Weights & Biases and SmartCow. Learn about Ultralytics, object detection metrics, and practical implementations for enhancing ML projects.