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| 1 | A Compress-Based Association Mining Algorithm for Large Dataset 显示文摘 | MAFRUZ ZAMAN ASHRAFI DAVID TANIAR KATE SMITH | 2003 | Lecture Notes in Computer Science2003，2660，： | 1 |
| 2 | Mining Hierarchical Negative Association Rules显示文摘 | David Taniar Wenny Rahayu | 2012 | International Journal of Computational Intelligence Systems2012，5，3： | 1 |
| 3 | Concurrency Control Issues in Grid Databases显示文摘 | David Taniar Sushant Goel | 2007 | Future Generation Computure Systems2007，23，1： | 1 |
| 4 | Mining hierarchical negative association rules显示文摘 | David Taniar Wenny Rahayu | 2012 | International Journal of Computational Intelligence Systems2012，5，3： | 1 |
| 5 | On Mining Movement Pattern from Mobile Users显示文摘 | David Taniar John Goh | 2007 | International Journal of Distributed Sensor Networks2007，，1： | 1 |
| 6 | Voronoibased range and continuous range query processing in mobile databases显示文摘 | Xuan Kefeng Zhao Geng David Taniar | 2009 | Journal of Computer and System Sciences IEEE AIAN2009，77，4： | 1 |
| 7 | MOBILE INFORMATION SYSTEMS显示文摘With the popularity of mobile infrastructures providing higher bandwidth and constant connection to the network from virtually anytime and everywhere,the way people use information resources is radically transformed.People can use mobile devices such as mobile phones,pocket PCs,laptops,etc.,to obtain services/applications which are based on the mobile | WANG Shangguang Ching-Hsien Hsu David Taniar Patrick Hung | 2015 | China Communications2015，12，12： | 0 |
| 8 | Diagnosis of COVID-19 Infection Using Three-Dimensional Semantic Segmentation and Classification of Computed Tomography Images显示文摘Coronavirus 19(COVID-19)can cause severe pneumonia that may be fatal.Correct diagnosis is essential.Computed tomography(CT)usefully detects symptoms of COVID-19 infection.In this retrospective study,we present an improved framework for detection of COVID-19 infection on CT images;the steps include pre-processing,segmentation,feature extraction/fusion/selection,and classification.In the pre-processing phase,a Gabor wavelet filter is applied to enhance image intensities.A marker-based,watershed controlled approach with thresholding is used to isolate the lung region.In the segmentation phase,COVID-19 lesions are segmented using an encoder-/decoder-based deep learning model in which deepLabv3 serves as the bottleneck and mobilenetv2 as the classification head.DeepLabv3 is an effective decoder that helps to refine segmentation of lesion boundaries.The model was trained using fine-tuned hyperparameters selected after extensive experimentation.Subsequently,the Gray Level Co-occurrence Matrix(GLCM)features and statistical features including circularity,area,and perimeters were computed for each segmented image.The computed features were serially fused and the best features(those that were optimally discriminatory)selected using a Genetic Algorithm(GA)for classification.The performance of the method was evaluated using two benchmark datasets:The COVID-19 Segmentation and the POF Hospital datasets.The results were better than those of existing methods. | Javaria Amin Muhammad Sharif Muhammad Almas Anjum Yunyoung Nam Seifedine Kadry David Taniar | 2021 | Computers, Materials & Continua2021，，8： | 0 |
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