Using machine learning for defect detection
نویسندگان
چکیده
In this paper we present an approach to defect detection in images based on machine learning algorithms. A qualitative model of defect has been devised based on human experience. A set of vision primitives measuring defect features has been deened. Objects in images candidate to be classiied as defects are submitted to automatic classiication, which is achieved with learning by examples algorithms. Results attained on a set of images from an industrial environment are presented and discussed.
منابع مشابه
Comparative Analysis of Machine Learning Algorithms with Optimization Purposes
The field of optimization and machine learning are increasingly interplayed and optimization in different problems leads to the use of machine learning approaches. Machine learning algorithms work in reasonable computational time for specific classes of problems and have important role in extracting knowledge from large amount of data. In this paper, a methodology has been employed to opt...
متن کاملUsing Machine Learning Algorithms for Automatic Cyber Bullying Detection in Arabic Social Media
Social media allows people interact to express their thoughts or feelings about different subjects. However, some of users may write offensive twits to other via social media which known as cyber bullying. Successful prevention depends on automatically detecting malicious messages. Automatic detection of bullying in the text of social media by analyzing the text "twits" via one of the machine l...
متن کاملFault Detection of Anti-friction Bearing using Ensemble Machine Learning Methods
Anti-Friction Bearing (AFB) is a very important machine component and its unscheduled failure leads to cause of malfunction in wide range of rotating machinery which results in unexpected downtime and economic loss. In this paper, ensemble machine learning techniques are demonstrated for the detection of different AFB faults. Initially, statistical features were extracted from temporal vibratio...
متن کاملA Hybrid Machine Learning Method for Intrusion Detection
Data security is an important area of concern for every computer system owner. An intrusion detection system is a device or software application that monitors a network or systems for malicious activity or policy violations. Already various techniques of artificial intelligence have been used for intrusion detection. The main challenge in this area is the running speed of the available implemen...
متن کاملEmotion Detection in Persian Text; A Machine Learning Model
This study aimed to develop a computational model for recognition of emotion in Persian text as a supervised machine learning problem. We considered Pluthchik emotion model as supervised learning criteria and Support Vector Machine (SVM) as baseline classifier. We also used NRC lexicon and contextual features as training data and components of the model. One hundred selected texts including pol...
متن کاملAutomatic road crack detection and classification using image processing techniques, machine learning and integrated models in urban areas: A novel image binarization technique
The quality of the road pavement has always been one of the major concerns for governments around the world. Cracks in the asphalt are one of the most common road tensions that generally threaten the safety of roads and highways. In recent years, automated inspection methods such as image and video processing have been considered due to the high cost and error of manual metho...
متن کامل