Build - Local Datastore and Security in Parse Apps
Explore Parse Local Datastore for offline app functionality and learn about Parse security features to protect user data and ensure safe app operations.
Creating Games with the Parse JavaScript SDK
Learn to create HTML5 games using Parse JavaScript SDK, based on Backbone.js. Explore Parse Objects, Cloud Code, game matching, and Unity integration for efficient app development.
Building Powerful Mobile Apps with Parse
Learn to build powerful mobile apps using Parse, covering data sharing, login, push notifications, and cloud integration for a comprehensive development experience.
Building Line of Business Apps with Parse
Learn to build business apps efficiently using Parse, covering data controls, validation, server-side logic, and UI components for rapid development and seamless data integration.
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.
Getting Started with Parse - Cloud-Based Platform for App Development
Learn to build engaging apps with Parse's cloud platform. Explore data APIs, social features, push notifications, and cloud code for efficient app development.
Parse Developer Day 2013 Keynote - Cloud Modules and Unity Integration
Explore Parse's latest features and roadmap, including Cloud Modules and Unity integration, presented by CEO Ilya Sukhar with an introduction from Mark Zuckerberg.
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.
Building the Elegoo Smart Robot Car - Arduino Based Robotics Project
Step-by-step guide to assembling an Arduino-based Elegoo Smart Robot Car, covering component overview, assembly process, and initial testing of this versatile educational robotics project.
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.
Speech-to-Intent on MCU: TinyML for Efficient Device Control - Lecture 6
Learn efficient speech-to-intent techniques for MCUs, focusing on direct parsing of user utterances into actionable output. Explore model training, deployment, and testing on Wio Terminal.
Power Efficient Neural Network Based Hardware Architecture for Biomedical Applications
Power-efficient neural network hardware architecture for biomedical applications, focusing on sleep apnea detection using ECG and SpO2 data. Introduces SABiNN technique for reduced power consumption and compact design while maintaining accuracy.
Software-Driven TinyML Hardware Co-Design for AI Power Smart Devices
Explore software-hardware co-design for efficient TinyML systems, focusing on processing-in-memory accelerators to reduce power consumption and enhance AI inference in smart devices.
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.
On-Device Continuous Event-Driven Deep Learning to Avoid Model Drift
Explore on-device continuous event-driven deep learning to prevent model drift in AIoT applications, focusing on real-time data adaptation without user intervention for industrial use cases.
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.
Neuromorphic Intelligence and Learning in Robotics
Explore neuromorphic engineering for efficient AI in robotics, focusing on on-chip learning and processing algorithms using Intel's Loihi 2 chip and the Lava software framework.
TinyML Auto ML Deep Dive: GAPflow - From TFLite and ONNX to Optimized C Code
Explore GAPflow: transform neural networks into optimized C code for ultra-low-power GAP processors. Learn quantization, validation, and memory allocation for efficient AI deployment on energy-constrained devices.
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.
On-Device Learning Under 256KB Memory - Challenges and Solutions for IoT Devices
Explore on-device learning for IoT devices with limited memory. Learn techniques for efficient model adaptation, quantization-aware scaling, and sparse updates to enable continuous learning on tiny hardware.