Search Results - (( developing learning morphology algorithm ) OR ( java implication based algorithm ))

Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review by Musri, Nabila, Christie, Brenda, Ichwan, Solachuddin Jauhari Arief, Cahyanto, Arief

“…Identifying caries with a deep convolutional neural network-based detector enables the operator to distinguish changes in the location and morphological features of dental caries lesions. Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects. …”
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The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques by Mohammad Syawaludin Syafiq, Hassan

“…In this study, a tracking algorithm is developed by means of image processing technique in detecting ambulance. …”
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A hybrid chromaticity-morphological machine learning model to overcome the limit of detecting newcastle disease in experimentally infected chicken within 36 h by Bakar, Mohd Anif A.A., Ker, Pin Jern, Tang, Shirley G.H., Arman Shah, Fatin Nursyaza, Mahlia, T. M.Indra, Baharuddin, Mohd Zafri, Omar, Abdul Rahman

“…This work demonstrates a promising methodology in developing machine learning algorithm using hybrid chromaticity-morphological features for early detection of virus-infected chickens, contributing to the goal of a sustainable and healthier planet.…”
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar M.A.A.A., Ker P.J., Tang S.G.H., Baharuddin M.Z., Lee H.J., Omar A.R.

Morphological segmentation and analysis of Bangla text by Saha, G C, Saha, Hasi, Che Mat, Ruzinoor, Khan, Nur Hossain, Sarker, Bappa

“…This paper deals with lexicon and system development for word segmentation in Bangla language.Our goal in this paper is to develop a morphological segmentation algorithm that can work well for Bangla and to address the problem of unsupervised word segmentation across different languages.From a hand-corrected Bangla corpus, 5000 popular words were segmented into suffixes, prefixes and roots manually.These were the sample lexicon used as seed for next step. …”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

“…Results of studying color segmentation using machine-learning algorithm and color space analysis is presented in this thesis. …”
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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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An annotated image dataset of urban insects for the development of computer vision and deep learning models with detection tasks by Lima, Min Hui, Chan, Hiang Hao, Ong, Song Quan

“…A large image dataset with the aim of developing an insect recognition algorithm like YOLO. …”
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Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique by Jais, Fatin Nabihah, Che Azemin, Mohd Zulfaezal, Hilmi, Mohd Radzi, Mohd Tamrin, Mohd Izzuddin, Mohd. Kamal, Khairidzan

“…Conclusion. Machine learning algorithms can produce a highly accurate postsurgery classification model of BCVA changes using pterygium characteristics.…”
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A Review: Recent Automatic Algorithms for the Segmentation of Brain Tumor MRI by Rafi, A., Khan, Z., Aslam, F., Jawed, S., Shafique, A., Ali, H.

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Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab by Wahhab, Hayan Tareq Abdul

“…In particular, this research focuses on Acute Leukemia, which can be of two distinct types (ALL, AML), with the main objective to develop a methodology to detect and classify Acute Leukemia blast cells into one of the above types based on image processing and machine learning techniques using peripheral blood smear images. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Neural network paradigm for classification of defects on PCB by Heriansyah, Rudi, Syed Al-Attas, Syed Abdul Rahman, Zabidi, Muhammad Mun'im Ahmad

“…A new technique is proposed to classify the defects that could occur on the PCB using neural network paradigm. 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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New Instances Classification Framework On Quran Ontology Applied To Question Answering System by Utomo, Fandy Setyo, Suryana, Nanna, Azmi, Mohd Sanusi

“…Instances classification with the small dataset for Quran ontology is the current research problem which appears in Quran ontology development. The existing classification approach used machine learning: Backpropagation Neural Network. …”
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An automated pipeline for constructing 3D models of monogenean hardparts using machine learning technique for landmarks detection / Teo Bee Guan by Teo , Bee Guan

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Classification of Citrus (Rutaceae) by Using Image Processing by Najwa Bari'ah Mohd Tabri

“…A machine learning algorithms, SVM have been used to build species identification models. …”
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ScannerVision: Scanner-based image acquisition of medically important arthropods for the development of computer vision and deep learning models by Ong, Song Quan, Nathan Pinoy, Lim, Min Hui, Kim Bjerge, Francisco Javier Peris-Felipo, Rob Lind, Jordan P. Cuff, Samantha M. Cook, Toke Thomas Høye

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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…For many morphological leaf features pre-defined by botanists, researchers use hand-engineering approaches for their characterization. …”
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