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Some of the next articles are maybe not open access.

Getting Started with OpenCV

2021
Since Chapter 1, you’ve come a long way in the world of home automation using Raspberry Pi. At this point, you have learned about the Pi and the various methods to automate your home. You have also seen how to build your own hardware to control appliances wirelessly. In the previous chapter, you controlled the appliances using voice commands.
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OpenCV on the JavaVM

2018
The very core of OpenCV is a multidimensional matrix object named Mat. Mat is going to be our best friend all along this book. Input objects are Mat, operations are run on Mat, and the output of our work is also going to be Mat.
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An Introduction to OpenCV

2018
We’ve come a long way since the first chapters introducing the Raspberry Pi. At this point, you have learned about the Pi and the Arduino. You’ve learned how to program both boards. You’ve worked with sensors and motors. You’ve built your robot and programmed it to roam around and to follow a line.
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OpenCV and Perception

2022
David Allen Blubaugh   +3 more
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Smart Trainer using OpenCV

2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA), 2023
Harsha Vardhan Reddy Podduturi   +5 more
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An OpenCV-Based Approach for Automated Cardiac Rhythm Measurement in Zebrafish from Video Datasets

Biomolecules, 2021
Syed Muhammad Ali Farhan   +2 more
exaly  

Video Processing from a Virtual Unmanned Aerial Vehicle: Comparing Two Approaches to Using OpenCV in Unity

Applied Sciences (Switzerland), 2022
Lidia María Belmonte   +2 more
exaly  

Marine-Hydraulic-Oil-Particle Contaminant Identification Study Based on OpenCV

Journal of Marine Science and Engineering, 2022
Hongpeng Zhang
exaly  

LANELINE DETECTION USING OPENCV

International Scientific Journal of Engineering and Management
Abstract - In view of the huge computing, poor anti-interference ability of traditional detection algorithm, it does not meet the requirement of the vehicle system, for which this paper proposed a lane detection method based on OpenCV. Preprocessing image in the OpenCV environment, adopting LMedSquare(Least Median Square) idea to select the best subset
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