Search Results - (( java implementation based algorithm ) OR ( image classification cell algorithm ))
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1
An Investigation of Image and Video Classification Algorithm for White Blood Cells Detection in Real Time View
Published 2015“…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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Final Year Project -
2
HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…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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Final Year Project -
3
FLUORESCENCE INTENSITY POSITIVITY CLASSIFICATION OF HEP-2 CELLS IMAGES USING FUZZY LOGIC
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Final Year Project -
4
RSA Encryption & Decryption using JAVA
Published 2006“…Today, with online marketing, banking, healthcare and other services, even the average householder is aware of encryption. The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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5
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
6
HEp-2 cell images classification based on statistical texture analysis and fuzzy logic
Published 2014“…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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Conference or Workshop Item -
7
Blood cell image segmentation using unsupervised clustering techniques
Published 2009“…The aim of our research is to develop an effective algorithm for segmentation of the blood cell images. …”
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8
Classification red blood cells using support vector machine
Published 2023“…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…”
Conference Paper -
9
An Adaptive Fuzzy Contrast Enhancement Algorithm with Details Preserving
Published 2014“…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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Article -
10
Modified Piecewise Linear Mapping Contrast Enhancement And Local Otsu Segmentation Methods For Hep-2 Cell Images
Published 2019“…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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Thesis -
11
Classification Of Cervical Cancer Stage From Pap Smear Tests
Published 2019“…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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Final Year Project -
12
Red blood cells classification with sharpening segmentation and mask R-CNN
Published 2023“…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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13
Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab
Published 2015“…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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Thesis -
14
An Intelligent Detection System for Rheumatoid Arthritis (RA) Disease using Image Processing
Published 2014“…The algorithm tested on the publicly available Mivia Hep-2 Cell image dataset. …”
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Final Year Project -
15
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…The main challenges of implementing ANPR algorithm on mobile phone are how to produce a higher coding efficiency, lower computational complexity, and higher scalability. …”
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16
Lung cancer medical images classification using hybrid CNN-SVM
Published 2021“…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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17
Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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Thesis -
18
Geometric Feature Extraction for Identification and Classification of the Overlapping Cells for Leukaemia
Published 2018“…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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Thesis -
19
MITOTIC HEp-2 CELL RECOGNITION USING LOCAL BINARY PATTERN (LBP) AND k-NEAREST NEIGHBOUR (k-NN) CLASSIFIER
Published 2014“…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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Final Year Project -
20
Hybrid of convolutional neural network algorithm and autoregressive integrated moving average model for skin cancer classification among Malaysian
Published 2021“…However, these machine learning methods cannot get the deep features from network flow which resulting in low accuracy and the pretrained DNN has the complex network with a huge number of parameters causes the limited classification accuracy. This paper focuses on the classification of skin cancer to identify whether it is basal cell carcinoma, melanoma or squamous cell carcinoma by using the development of hybrid convolutional neural network algorithm and autoregressive integrated moving average model (CNN-ARIMA). …”
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