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Learn to track objects using OpenCV on Jetson Nano, controlling a camera with servos to keep the target centered. Implement computer vision and robotics skills for real-time object tracking applications.
Learn to measure the speed of sound using an Arduino and HC-SR04 sensor. Practice dimensional analysis, unit conversion, and apply math skills in a practical, hands-on project.
Learn to control servos with the Jetson Nano using PCA9685, including setup, programming, and movement control. Gain hands-on experience in robotics and automation with this practical tutorial.
Learn to connect and program the HC-SR04 ultrasonic sensor with Arduino, measuring ping travel time and exploring sensor functionality through hands-on exercises and practical demonstrations.
Learn to track objects using contours in OpenCV on the Jetson Nano. Explore masking, fine-tuning, and bounding rectangles for effective object detection and tracking in AI applications.
Learn to track objects in OpenCV using HSV color space, including image conversion, parameter setting with trackbars, and creating foreground/background masks for effective color-based object tracking.
Learn to measure temperature and humidity using the DHT11 sensor with Arduino. Covers library installation, wiring, code setup, and troubleshooting for accurate environmental data collection.
Learn to build a simple calculator with LCD display using Arduino, covering input handling, arithmetic operations, and formatted output.
Learn to create and manipulate live moving watermarks in OpenCV using threshold and masking techniques for video feeds on the Jetson Nano.
Explore thresholding and masking techniques in OpenCV to manipulate image foregrounds and backgrounds independently, enhancing your AI skills on the Jetson Nano platform.
Learn to create Region of Interest in OpenCV using mouse events and clicks, enhancing image processing capabilities for AI applications on Jetson Nano.
Learn to work with Region of Interest (ROI) in OpenCV on Jetson Nano, including setting up rectangles, creating and colorizing ROIs, and animating cuts for enhanced image processing capabilities.
Learn to build a self-leveling platform using Arduino, BNO055 sensor, and servos. Hands-on tutorial covers circuit assembly, mechanical construction, and servo control for tilt stabilization.
Learn to work with Region of Interest (ROI) in OpenCV for AI applications on Jetson Nano, including live video processing and practical examples.
Visualize 3D rotations using quaternions in Vpython. Learn to simulate rigid body movements, integrate Arduino with BNO055 IMU sensor, and convert quaternions to Euler angles for accurate representation.
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