Tag: computer vision
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Aluminum casting quality control using computer vision techniques
Automated X-ray systems are improving quality through multiple objective inspections, and reducing labor costs, and increasing productivity and consistency by revising involved processes. This paper proposes a novel approach to train a YOLO-based model for detecting defects in aluminum castings. Deep learning-based models are garnering more attention in the aluminum castings industry every day, and…
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How Backbone Works
Backbone is a network that extracts a feature map of the input image , the map is then utilized by the rest of the network. The purpose of this paper is to introduce the concept of backbone and how it fits in the AIEX platform.
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Computer Vision Evaluation Metrics
This article examines the different metrics used to evaluate machine vision models, and the metrics implemented on the AIEX platform.
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How Object Detection Works
Object detection is focused on identifying objects of interest in digital photographs using a computer vision model. In this paper, we’ll explore this technology and explain the most common algorithms suitable for object detection.
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Using Computer Vision to Identify and Count Blood Cells helps in medical diagnosis
Identification and quantification of complete blood cells (CBCs) is often an essential clinical test to monitor a patient’s health. The conventional method suffers from time-consuming and erroneous procedures, is dependent on the skill of clinical laboratorians, and is affected by the quality and precision of laboratory equipment. This paper introduces a “you only look once”…
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The printing industry is joining the 4.0th industrial revolution. Spring is coming!
Deep Learning algorithms were used to automate the quality control of printing processes. The developed model can automatically classify and detect some printing defects with an accuracy rate of 98.4%. This approach makes it easier to persuade business leaders to think of deep architecture as a possible solution for their challenges.
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Logistics monitoring is a piece of cake by computer vision
Computer vision (CV) in logistics can promote the ability of manufacturers and managers to detect problems and optimize processes. The company owners can take advantage of artificial intelligence (AI) in logistics to enhance efficiency and effectiveness by accelerating manual processes as well as improving safety while significantly reducing operational costs.
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Intelligent machines revolutionize quality assurance in the automotive industry
The auto manufacturing industry has been integrating AI and CV into its processes. Car companies use Computer-generated imagery (CGI) to design ideal cars. This novel approach creates some difficulties with human-operated quality assurance (QA). The proposed QA system relies on a considerably smaller labeled dataset to detect defects in virtual car renderings.
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Computer vision can help us with agriculture: A case study of defects in fruits
The growing world population constantly pushes the demand for agricultural products. More production means more efficient methods should be employed for product quality control, and the process should improve in accuracy and time. Artificial intelligence (AI), especially CV, is playing a critical role in replacing skilled staff with machines for quality inspection and classification.
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Introduction to Image Segmentation
Image Segmentation is one of the most crucial tasks performed by computer vision models. In this article, we discuss image segmentation and its application in various fields.