Quality Inspection of Dengue kits using YOLOv4 architecture
Akshat Sharma, Kaushik Sharma, Ashita Shetty, Shubham Shinde · International Journal for Research in Applied Science and Engineering Technology · 2022
Abstract: With the increasing advancements in Artificial Intelligence and its varied applications across multiple domains, the manufacturing industry is not left behind. Manufacturing and Production require a lot of labour force to ensure good quality end results. While this may be a necessity in the rudimentary stages of development, there is a way to cut down on this while checking the quality of the end product. This project aims at using the power of Artificial Intelligence, specifically Computer vision to create a quality inspecting tool that entails localizing and predicting the required objects in the image of the Dengue kit. This project highlights the entire process including simulation, design of conveyor belt and displays the final process of how both combined can help catalyse quality inspection by subtracting the manual crunch. Keywords: Artificial Intelligence, Inspection, Computer vision, Industry 4.0 Revolution, Object Detection, Yolov4