SURFACE DEFECT DETECTION WITH NEURAL NETWORKS

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Additive Manufacturing Defect Detection using Neural Networks

Currently defect detection in additive manufacturing is predominately done by traditional image processing, approximation, and statistical methods. Two important aspects of defect detection are edge detection and porosity detection. Both problems appear to be good candidates to apply machine learning. This project describes the implementation of neural networks as an alternative method for defe...

متن کامل

Apple Defect Detection and Quality Classification with MLP-Neural Networks

The initial analysis of a quality classification system for ‘Jonagold’ and ‘Golden Delicious’ apples is shown. Color, texture and wavelet features are extracted from the apple images. Principal components analysis was applied on the extracted features and some preliminary performance tests were done with single and multi layer perceptrons. Keywordscomputer vision; image processing; defect segme...

متن کامل

Surface Defect Detection with Histogram - Based

In this paper the performance of two histogram-based texture analysis techniques for surface defect detection is evaluated. These techniques are the co-occurrence matrix method and the local binary pattern method. Both methods yield a set of texture features that are computed from a small image window. The unsupervised segmentation procedure is used in the experiments. It is based on the statis...

متن کامل

Defect Detection in Composite Materials by Thermography and Neural Networks

Advanced composite materials offer high structural performances with a remarkable lightness and are used in all fields where this quality is particularly recommended (aeronautics, navy, car manufacturing, etc.). The increasing diffusion of these materials has led to the need for the control of the manufacturing processes and to the wide use of inspections of structural integrity conditions, dur...

متن کامل

Aircraft Fuselage Defect Detection using Deep Neural Networks

To ensure flight safety of aircraft structures, it is necessary to have regular maintenance using visual and nondestructive inspection (NDI) methods. In this paper, we propose an automatic image-based aircraft defect detection using Deep Neural Networks (DNNs). To the best of our knowledge, this is the first work for aircraft defect detection using DNNs. We perform a comprehensive evaluation of...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: System technologies

سال: 2020

ISSN: 2707-7977,1562-9945

DOI: 10.34185/1562-9945-1-126-2020-10