Search Results - (( image classification cell algorithm ) OR ( code classification problems algorithm ))

An Investigation of Image and Video Classification Algorithm for White Blood Cells Detection in Real Time View by Abu Kasim, Nabeela

“…The new approach used in separating it by using image classification algorithm to separate the white blood cells from the blood capillaries and it will be done live from a video. …”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

“…A working classification algorithm is developed by using MATLAB and the Fuzzy Logic Toolbox to differentiate and classify the staining pattern of HEp-2 cell images. …”
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FLUORESCENCE INTENSITY POSITIVITY CLASSIFICATION OF HEP-2 CELLS IMAGES USING FUZZY LOGIC by ABANG SAZALI, DAYANG FARZANAI

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HEp-2 cell images classification based on statistical texture analysis and fuzzy logic by Jamil, N.F.B., Faye, I., May, Z.

“…This paper proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Blood cell image segmentation using unsupervised clustering techniques by Tuan Muda, Tuan Zalizam, Abdul Salam, Rosalina

“…The aim of our research is to develop an effective algorithm for segmentation of the blood cell images. …”
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Classification red blood cells using support vector machine by Akrimi J.A., Suliman A., George L.E., Ahmad A.R.

“…Cells; Classification (of information); Cytology; Diagnosis; Feature extraction; Image processing; Image segmentation; Imaging techniques; Medical imaging; Support vector machines; Classifier algorithms; Clinical diagnosis; Confusion matrices; Image processing technique; Mean Filte; Red blood cell; Retrieval systems; SVM; Blood…”

An Adaptive Fuzzy Contrast Enhancement Algorithm with Details Preserving by Jing, Rui Tang, Mat Isa, Nor Ashidi

“…In addition, the experiments using cervical cell images and HEp-2 cell images showed great potential of the AFCEDP technique as a technique for enhancing medical microscopic images.…”
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Comparative Analysis of Cervical Cell Classification Using Machine Learning Algorithms by Wan Azani Mustafa, Khalis Khiruddin, Khairur Rijal Jamaludin, Firdaus Yuslan Khusairi, Shahrina Ismail

Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images by Baharom, Mohamad Shahrul Affendi

“…However, some of the image suffers from texture’s cell loss. On the other hand, the proposed segmentation method capable to segment cell and isolate most of the combined cell. …”
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Classification Of Cervical Cancer Stage From Pap Smear Tests by Sendal, Ken Irok

“…The performance of the proposed classification algorithm gave satisfactory results of accuracy, 91.9% for KNN classification and 95.0% for SVM classification.…”
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Red blood cells classification with sharpening segmentation and mask R-CNN by Arianti, Nunik Destria, Muda, Azah Kamilah, Ahmad, Norashikin

“…This paper proposes classification using sharpening segmentation combined with the algorithm mask R-CNN to increase the accuracy of calculating the number of RBCs. …”
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Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab by Wahhab, Hayan Tareq Abdul

“…Tettamanti Research Center for childhood leukemia and hematological diseases, Italy. The image segmentation addressed several key issues in blast cells segmentation including, the blast cell localization, sub-imaging, color variation and segregation of touching cells. …”
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An Intelligent Detection System for Rheumatoid Arthritis (RA) Disease using Image Processing by Hajyyev, Abdyrahym

“…The algorithm tested on the publicly available Mivia Hep-2 Cell image dataset. …”
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Lung cancer medical images classification using hybrid CNN-SVM by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Vanessa, Penshie, Hamada Rasheed Hassan, Al-Absi

“…This algorithm is capable of automatically classifying and analyzing each lung image to check if there is any presence of cancer cells or not. …”
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Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

“…Novices tend to refer to source codes examples and adapt the source codes to the problem given in their assignments. …”
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Scene classification for aerial images based on CNN using sparse coding technique by Qayyum, A., Malik, A.S., Saad, N.M., Iqbal, M., Faris Abdullah, M., Rasheed, W., Rashid Abdullah, T.A., Bin Jafaar, M.Y.

“…Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. …”
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Geometric Feature Extraction for Identification and Classification of the Overlapping Cells for Leukaemia by Kiu, Siew Ming

“…Overlapping cell identification and classification of microscopic blood cell image is proposed to increase the accuracy of the number of automated counting and the percentage of the overall accuracy. …”
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Maldroid- attribute selection analysis for malware classification by Rahiwan Nazar, Romli, Mohamad Fadli, Zolkipli, Mohd Zamri, Osman

“…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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Scene classification for aerial images based on CNN using sparse coding technique by Qayyum A., Malik A.S., Saad N.M., Iqbal M., Faris Abdullah M., Rasheed W., Rashid Abdullah T.A., Bin Jafaar M.Y.

MITOTIC HEp-2 CELL RECOGNITION USING LOCAL BINARY PATTERN (LBP) AND k-NEAREST NEIGHBOUR (k-NN) CLASSIFIER by Mahmod, Noor Fatihah

“…Therefore the ability to detect mitotic cells is acquired to develop Computer-Aided Diagnosis (CAD) system in IIF to support the specialists form image acquisition up to image classification. …”
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