Search Results - (( processing defect classification algorithm ) OR ( java adaptation optimization algorithm ))

Evaluation of the Transfer Learning Models in Wafer Defects Classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund, Lim, Shi Xuen

“…The key metrics for the evaluation are classification accuracy, classification precision and classification recall. 855 images were used to train and test the algorithms. …”
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The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

“…However, limitations such as robustness and difficulty in setting up the parameters required for image processing algorithm encourages the investigation in using Deep learning classification in detecting the wafer defects. …”
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

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A cascading fuzzy logic with image processing algorithm-based defect detection for automatic visual inspection of industrial cylindrical object’s surface by Ali, Mohammed A. H., Au, Kai Lun

“…This paper proposes a cascading fuzzy logic algorithm with image processing technique for defect detection and classification on the lateral surface of industrial cylindrical object using a camera and multiple flat mirrors. …”
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Evaluation of the machine learning classifier in wafer defects classification by Jessnor Arif, Mat Jizat, Anwar, P. P. Abdul Majeed, Ahmad Fakhri, Ab. Nasir, Zahari, Taha, Yuen, Edmund

“…Each image went through the embedding process by InceptionV3 algorithms before the evaluated classifier classifies the images.…”
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Neural network paradigm for classification of defects on PCB by Heriansyah, Rudi, Syed Al-Attas, Syed Abdul Rahman, Zabidi, Muhammad Mun'im Ahmad

“…The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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Design and Development of Artificial Intelligence (Al)-Based Desicion Support System For Manufacturing Applications by Lim , Chee Peng

“…Further work will focus on ascertaining the stability of the FAM network in defect classification, as well as on improving the overall performance of the defect detection algorithms developed in this project. …”
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Classification of metal screw defect detection using FOMO on edge impulse / Muhammad Imran Daing by Daing, Muhammad Imran

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Machine learning application for concrete surface defects automatic damage classification by Syahrul Fithry Senin, Khairullah Yusuf, Amer Yusuf, Rohamezan Rohim

“…Therefore, a Machine Learning classifier for concrete surface defect classification using the Discriminant Analysis Classifier was introduced to more accurately extract the types of concrete surface defects information from the digital images. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Deep learning algorithm and IoT based system for Photovoltaic (PV) defect images classification by Mazlan, Nurul Atikah

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Enhanced Image Classification for Defect Detection on Solar Photovoltaic Modules by Wiliani, Ninuk

“…However, high similarity of characteristics among the shapes and textures has been a major challenge in defect classification process. The objective of this research was to develop and analyse feature extraction used for classification techniques for defect detection of solar photovoltaic modules surfaces. …”
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Evolutionary Fuzzy ARTMAP Neural Networks for Classification of Semiconductor Defects by Zuwairie, Ibrahim, Tan, Shing Chiang, Watada, Junzo, Marzuki, Khalid

“…Wafer defect detection using an intelligent system is an approach of quality improvement in semiconductor manufacturing that aims to enhance its process stability, increase production capacity, and improve yields. …”
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Hybrid multilayered perceptron network for classification of bundle branch blocks by Megat Syahirul Amin, Megat Ali, Ahmad Nasrul, Norali, Aisyah Hartini, Jahidin

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Identification of weld defect through the application of denoising method to the sound signal acquired during pulse mode laser welding by Yusof, M. F.M., Quazi, M. M., Aleem, S.A.A., Ishak, M., Ghazali, M. F.

“…This paper describes the improvement of weld defect identification achieved by incorporating Z-score-based thresholding into the wavelet denoising algorithm for the pre-processing of sound signals. …”
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Automated system for concrete damage classification identification using various classification techniques in machine learning / Nur Haziqah Mat ... [et al.] by Mat, Nur Haziqah, Ahmad Zahida, Athifa Aisha, Abdul Malik, Siti Nurhaliza, Azmadi, Nur Athirah Syuhada, Senin, Syahrul Fithry

“…This invention can recognize a certain damage while the classification of defects is classified according to the features extracted from the images by using GLCM algorithm. …”
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A three dimensional (3D) vision based defect inspection system for gluing application by Harun, Mohamad Haniff

“…Data for all the process are recorded to prove that this algorithm made improvement with the previous research.…”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee by Chong , Hue Yee

“…Different types of metaheuristic optimization tools have their unique features which vary from others and hence lead to different suitability in the particular application. Two metaheuristic algorithms i.e., Harmony Search (HS) and Gravitational Search Algorithm (GSA), are selected to integrate separately with a Radial Basis Function Network with Dynamic Decay Adjustment (RBFN-DDA) to perform condition monitoring in industrial processes. …”
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Aerial imagery paddy seedlings inspection using deep learning by Anuar, Mohamed Marzhar, Abdul Halin, Alfian, Perumal, Thinagaran, Kalantar, Bahareh

“…One of the disadvantages is that the studies aim to detect and count all the paddy seedlings to determine planting density. The defective paddy seedlings’ locations are not pointed out to help farmers during the sowing process. …”
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Enhancement of weld penetrations classification model performance through the implementation of denoising methods towards the acquired acoustic and optical signals during laser bea... by Aleem, S.A.A., Mohd Fadhlan, Mohd Yusof, M., Ishak, F. R. M., Romlay, I., Ishak

“…This project aims to enhance a classification model to estimate the weld penetration conditions of LBW by employing the EMD-Z-score (EMD-ZS) and spectral averaging (SA) denoising algorithm in the pre-processing stage. …”
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