Essays about: "Defect Detection"
Showing result 1 - 5 of 54 essays containing the words Defect Detection.
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1. A comparison between random testing and adaptive random testing
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : Software testing is essential for quality assurance, with automated techniques such as random testing and adaptive random testing being cost-effective solutions compared to others. Adaptive random testing seeks to enhance random testing, and there is a conception that adaptive random testing always should replace random testing. READ MORE
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2. Data Augmentations for Improving Vision-Based Damage Detection : in Land Transport Infrastructure
University essay from KTH/Lantmäteri – fastighetsvetenskap och geodesiAbstract : Crack, a typical term most people know, is a common form of distress or damage in road pavements and railway sleepers. It poses significant challenges to their structural integrity, safety, and longevity. Over the years, researchers have developed various data-driven technologies for image-based crack detection in road and sleeper applications. READ MORE
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3. Quality Control: Detect Visual Defects on Products Using Image Processing and Deep Learning
University essay from Malmö universitet/Fakulteten för teknik och samhälle (TS)Abstract : Computer vision, a prominent subfield of artificial intelligence, has gained widespread util-ization in diverse domains such as surveillance, security, and robotics. This research en-deavors to develop an semi-automated defect detection system serving as a quality controlassurance mechanism for Nolato MediTor, a manufacturing company within the medicaldevice industries engaged in the production of anesthesia breathing bags. READ MORE
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4. Semi-supervised anomaly detection in mask writer servo logs : An investigation of semi-supervised deep learning approaches for anomaly detection in servo logs of photomask writers
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Semi-supervised anomaly detection is the setting, where in addition to a set of nominal samples, predominantly normal, a small set of labeled anomalies is available at training. In contrast to supervised defect classification, these methods do not learn the anomaly class directly and should have better generalization capability as new kinds of anomalies are introduced at test time. READ MORE
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5. Quality Control in Aluminium Profiles : Non-destructive Methods using Non-linear Ultrasonic
University essay from Blekinge Tekniska Högskola/Institutionen för maskinteknikAbstract : When aluminium profiles are manufactured, defects may arise, especially when theprofiles are manufactured through extrusion. During the extrusion process, thesedefects occur on parts of the extruded material because of contaminates that needto be found. READ MORE