Search Results - (( mobile evaluation cell algorithm ) OR ( image classifications _ algorithm ))
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1
Bacterial image analysis using multi-task deep learning approaches for clinical microscopy
Published 2024“…Methods Three object detection networks of DL algorithms, namely SSD-MobileNetV2, EfficientDet, and YOLOv4, were developed to automatically detect Escherichia coli (E. coli) bacteria from microscopic images. …”
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Performance evaluation of LTE scheduling techniques for heterogeneous traffic and different mobility scenarios
Published 2015“…In this paper five scheduling algorithms were investigated and their performance was evaluated in terms of Fairness Index, Peak Throughput, Average Throughput and Edge Cell User Throughput. …”
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Performance evaluation of LTE scheduling techniques for heterogeneous traffic and different mobility scenarios
Published 2014“…In this paper five scheduling algorithms were investigated and their performance was evaluated in terms of Fairness Index, Peak Throughput, Average Throughput and Edge Cell User Throughput. …”
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Proceeding Paper -
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…Therefore, an improved feature extraction and selection for sky image classification (FESSIC) algorithm is proposed. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. …”
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An integrated priority-based cell attenuation model for dynamic cell sizing
Published 2012“…A new, robust integrated priority-based cell attenuation model for dynamic cell sizing is proposed and simulated using real mobile traffic data.The proposed model is an integration of two main components; the modified virtual community – parallel genetic algorithm (VC-PGA) cell priority selection module and the evolving fuzzy neural network (EFuNN) mobile traffic prediction module.The VC-PGA module controls the number of cell attenuations by ordering the priority for the attenuation of all cells based on the level of mobile level of mobile traffic within each cell.The EFuNN module predicts the traffic volume of a particular cell by extracting and inserting meaningful rules through incremental, supervised real-time learning.The EFuNN module is placed in each cell and the output, the predicted mobile traffic volume of the particular cell, is sent to local and virtual community servers in the VC-PGA module.The VC-PGA module then assigns priorities for the size attenuation of all cells within the network, based on the predicted mobile traffic levels from the EFuNN module at each cell.The performance of the proposed module was evaluated on five adjacent cells in Selangor, Malaysia. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
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Thesis -
8
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza
Published 2024“…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images
Published 2012“…The improved PCB defect classification algorithm has been applied to real PCB images to successfully classify all of the defects. …”
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Inter system handoff management in cellular mobile networks / Syamil Khalid
“…This paper presents a handoff technique which supports mobility between dissimilar networks. The boundary cell of cellular network system is designed by using MATLAB design software. …”
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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
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Laser-induced backscattering imaging for classification of seeded and seedless watermelons
Published 2017“…The LDA and kNN-based algorithms also obtained quite high classification accuracies with all the accuracies above 90%. …”
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Automatic classification of medical x-ray images
Published 2013“…Image representation is one of the major aspects of automatic classification algorithms. …”
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Inter-system handoff management in mobile cellular networks / Syamil Khalid
Published 2011“…The theoretical analysis and simulation result are studied to evaluate the handoff parameters and signal strength of mobility.…”
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16
Region-growing based segmentation and bag of features classification for breast ultrasound images
Published 2017“…In conclusion, region growing segmentation and Bag of features classification able to perform well in ultrasound image.…”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…It involves identifying and isolating relevant information from the images that classification algorithms can use to distinguish between different fruit categories. …”
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A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim
Published 2015“…This study presents an algorithm for nosologic segmentation of primary brain tumors on Magnetic Resonance Imaging (MRI) brain images. …”
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Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image
Published 2014“…In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. …”
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