Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

“…Most such models are constructed using statistical or machine learning techniques. …”
Get full text
Get full text
Get full text

A Highly Efficient And Automated Approach To Identifying And Classifying Urban Traffic Images Using Self Organizing Maps and Artificial Intelligence. (c2006) by Bey, Hisham Mardam

Get full text
Get full text

Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

Automatic image quality evaluation in digital radiography using a modified version of the IAEA radiography phantom allowing multiple detection tasks by Ioannis A. Tsalafoutas (14776939)

“…<h3>Purpose</h3><p dir="ltr">To evaluate image quality (IQ) of for‐processing (raw) and for‐presentation (clinical) radiography images, under different exposure conditions and digital image post‐processing algorithms, using a phantom that enables multiple detection tasks.…”

A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models by Azar, Danielle

“…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…”
Get full text
Get full text
Get full text

An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

“…Results Results show that our approach out-performs the machine learning algorithm C4.5 as well as random guessing. …”
Get full text
Get full text
Get full text

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth, Kunhoth

“…This work proposes various machine learning methods, including transfer learning via fine-tuning, transfer learning via feature extraction, ensembles of deep convolutional neural network (CNN) models, and fusion of CNN features, to develop a preliminary dysgraphia diagnosis system based on handwritten images. …”
Get full text
Get full text
Get full text

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children by Jayakanth Kunhoth (14158908)

“…This work proposes various machine learning methods, including transfer learning via fine-tuning, transfer learning via feature extraction, ensembles of deep convolutional neural network (CNN) models, and fusion of CNN features, to develop a preliminary dysgraphia diagnosis system based on handwritten images. …”

Machine Learning Model for a Sustainable Drilling Process by Alsaidi, Ola

Get full text

Learning-Based Spectrum Sensing and Access for Cognitive Radio Systems by Shehabeldin, Menatalla Diaaeldin

Get full text

DoFP-ML: A Machine Learning Approach to Food Quality Monitoring Using a DoFP Polarization Image Sensor by Maen Takruri (10873368)

Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

Subjects:

Detection of Depression in Arabic Social Media: A Comparison of Traditional and Modern Machine Learning Algorithms by ALSHEHHI, OMAR KHALID HAMAD

Get full text

Hybrid Deep Learning-based Models for Crop Yield Prediction by Alexandros Oikonomidis (12050497)

“…In this study, we developed deep learning-based models to evaluate how the underlying algorithms perform with respect to different performance criteria. …”

Classifying Maqams of Qur'anic Recitations Using Deep Learning by Shahriar, Sakib

“…Technological advancement can be utilized for automatic classification of these melodies which can then be used by students for self-learning. Using state-of-the-art deep learning algorithms, this research focuses on the classification of the eight popular maqamat (plural of maqam). …”
Get full text

Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

“…Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …”
Get full text

Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…As a result of the models’ evaluation, a hybrid DL model is proposed that combines the best characteristics of the baseline models CNN, BLSTM and GRU for identifying cyberbullying. …”
Get full text

Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…As a result of the models’ evaluation, a hybrid DL model is proposed that combines the best characteristics of the baseline models CNN, BLSTM and GRU for identifying cyberbullying. …”
Get full text
Get full text

Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques by Abu Zitar, Raed

“…Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. …”
Get full text

A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model by Md. Nazmul Islam Shuzan (16888827)

“…The best ML model and the best feature selection algorithm combination were fine-tuned to optimize its performance using hyperparameter optimization. …”