Using FFMPEG to Encode-Decode Video for Offline Video-Based Machine Learning
Learn to use FFMPEG for video encoding/decoding in machine learning, enabling frame-by-frame processing and video generation from individual images.
Generating Faces with a Generative Adversarial Networks - GAN in Keras-Tensorflow 2.0
Learn to implement a Generative Adversarial Network (GAN) from scratch using TensorFlow and Keras to generate realistic human faces, with step-by-step guidance and practical code examples.
Keras Convolutional Neural Networks for MNIST and Fashion MNIST
Explore convolutional neural networks for image processing, focusing on MNIST and Fashion MNIST datasets. Learn about CNN architecture, training, and evaluation for advanced deep learning applications.
The Deep Learning Revolution
Explore the evolution of deep learning, from its origins to modern applications, covering key milestones, breakthroughs, and future prospects in AI and neuroscience.
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.
Kickstarting Computer Vision with the OpenMV
Explore the journey of OpenMV, a computer vision project, from Hackaday Prize entry to successful product launch, overcoming challenges in manufacturing and community management.
Integral Images: Concept and Application in Spatial Algorithms
Learn about integral images for faster spatial partitioning and search algorithms, with a demonstration of object tracking implementation and practical coding examples.
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.
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.
Raspberry Pi Remote Camera with MotionEyeOS - Build a Surveillance System
Build a sophisticated motion-sensitive surveillance system using Raspberry Pi and motionEyeOS. Learn camera setup, motion detection, remote access, and advanced features for a customizable home security solution.
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.
In-memory Computing and Dynamic Vision Sensors for Internet of Video Things
Exploring neuromorphic technologies, dynamic vision sensors, and in-memory computing for energy-efficient IoT video applications, with focus on innovative solutions for intelligent transportation and unattended ground sensors.
Optimizing Data-Flow in Binary Neural Networks
Explore optimizing data flow in Binary Neural Networks, focusing on hardware efficiency, quantization techniques, and accuracy improvements for embedded systems.
Enabling On-Device Learning at Scale
Explore on-device learning techniques for AI personalization, including few-shot learning, continuous learning, and federated learning, addressing privacy and efficiency challenges in edge computing.
State of the TinyAutoML Market - Keynote
Explore the emerging tinyAutoML market, its challenges, opportunities, and potential impact on IoT and edge computing. Gain insights from industry experts on automating tiny machine learning applications.
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.
Next-Generation Deep-Learning Accelerators: From Hardware to System - tinyML Summit 2022
Explore next-gen deep learning accelerators, focusing on system-level challenges and opportunities in design, integration, and scheduling for future AI hardware advancements.
Implementing Real-time Vision AI Apps Using NVIDIA DeepStream SDK
Explore real-time video analysis with NVIDIA DeepStream SDK. Learn to build high-performance apps for IoT sensors, leveraging pre-trained models and optimized pipelines for various industries.
Grandmaster Series - Building a World-Class ML Model for Melanoma Detection
Learn how Kaggle Grandmasters built a world-class ML model for melanoma detection, outperforming average dermatologists. Discover key strategies in model architecture, augmentation, and training for accurate skin lesion classification.
NVIDIA Tools for Training and Deploying Intelligent Vision Applications at the Edge
Discover tools for training, building, and deploying intelligent vision applications at the edge using NVIDIA's suite for video analytics pipelines and IoT devices.
DeepStream SDK - Accelerating Real-Time AI-Based Video and Image Analytics
Accelerate real-time AI-based video and image analytics with DeepStream SDK. Learn about flexible deployment, architecture, and applications in retail, smart cities, manufacturing, and logistics.