Cyberbullying Detection in Arabic Text using Deep Learning حسب ALBAYARI, REEM RAMADAN SA’ID

"…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. …"
احصل على النص الكامل

Predicting Android Malware Using Evolution Networks حسب Chahine, Joy

"…Experimental studies clearly show a higher accuracy of our proposed approach in comparison with existing machine learning models, namely random forest, artificial neural network, decision tree, and logistic regression.…"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل

SemIndex: Semantic-Aware Inverted Index حسب Chbeir, Richard

احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل

A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education حسب Abu Zitar, Raed

"…As part of this work, two deep learning models are compared according to their performance. …"
احصل على النص الكامل

An efficient approach for textual data classification using deep learning حسب Abdullah Alqahtani (7128143)

"…Next, we employ machine learning algorithms: logistic regression, random forest, K-nearest neighbors (KNN), and deep learning algorithms: long short-term memory (LSTM), artificial neural network (ANN), and gated recurrent unit (GRU) for classification. …"

Predicting the Impact of Data Poisoning Attacks in Blockchain-Enabled Supply Chain Networks حسب Javed Butt , Usman

احصل على النص الكامل
احصل على النص الكامل

Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE حسب Ben Romdhane, Haifa

"…The validation of these results was performed using previous archaeological works as well as geological and geomorphological field surveys. The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
احصل على النص الكامل

Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context حسب SALIM, MAHA JAWDAT

"…A dataset generated by a digital learning platform used by a private school in Jordan is utilised. Various ML algorithms, such as Support Vector Machines, Logistic Regression, K-Nearest Neighbors, Naïve Bayes, Decision Trees, Random Forest, AdaBoost, Bagging, and Artificial Neural Networks are applied to predict student performance. …"
احصل على النص الكامل

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children حسب 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. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل

Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) حسب AL SHOUBAKI, HAMZA YOUNIS

"…We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …"
احصل على النص الكامل

Developing an online hate classifier for multiple social media platforms حسب Joni Salminen (7434770)

"…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …"

Utilization of AI to Predict Shear Strength Parameters of Soil Based on Their Physical Properties حسب AbdulGhafour, Husaen

احصل على النص الكامل

The use of multi-task learning in cybersecurity applications: a systematic literature review حسب Shimaa Ibrahim (22155739)

"…Most of the studies used supervised learning algorithms, and there were very limited studies that focused on other types of machine learning. …"

CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children حسب 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. …"

Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE حسب Ben-Romdhane, Haïfa

"…The validation of these results was performed using previous archaeological works as well as geological and geomorphological field surveys. The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …"
احصل على النص الكامل

Nonlinear Friction Identification of A Linear Voice Coil DC Motor حسب Takrouri, Mohannad Hashem

احصل على النص الكامل

Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems حسب Mahmood, Lubna Syeda

احصل على النص الكامل

Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks حسب Mohammed Almehdhar (22046597)

"…Our systematic review covers a range of AI algorithms, including traditional ML, and advanced neural network models, such as Transformers, illustrating their effectiveness in IDS applications within IVNs. …"

DASSI: differential architecture search for splice identification from DNA sequences حسب Shabir Moosa (14153316)

"…</p> <h2>Conclusions</h2> <p>We proposed the use of differential architecture search method (DASSI) to perform SS classification on raw DNA sequences, and discovered new neural network models with low number of tunable parameters and competitive performance compared with manually engineered architectures. …"

An intelligent approach to predicting the effect of nanoparticle mixture ratio, concentration and temperature on thermal conductivity of hybrid nanofluids حسب Ifeoluwa Wole-Osho (14151315)

"…A polynomial correlation model, the adaptive neuro-fuzzy inference system model and an artificial neural network model optimised with three different learning algorithms. …"