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2020 – today
- 2024
[j14]Mingzuoyang Chen
, Shadi Banitaan, Mina Maleki:
Pedestrian Group Re-Identification and Trajectory Prediction Through Zone-Based Clustering. IEEE Access 12: 101549-101562 (2024)- [j13]Bassam A. Abdelghani, Ahlam Al Mohammad, Jamal Dari, Mina Maleki, Shadi Banitaan:
Occupancy prediction: A comparative study of static and MOTIF time series features using WiFi Syslog data. Sustain. Comput. Informatics Syst. 44: 101040 (2024) - [c32]Ahlam Al Mohammad, Daniel Marku, John Reedy, Stephen Reedy, Mina Maleki, Shadi Banitaan:
Enhancing Indoor Positioning of Wireless Access Points using RSSI Fingerprints. EIT 2024: 1-8 - [c31]Benyamain Yacoob, Ethan Scheys, Eyiara Oladipo, Andre Price, Shadi Banitaan:
Using Machine Learning and Google Earth Engine to Understand Land Use and Land Cover Classifications and NO2 Levels in California. EIT 2024: 410-417 - [c30]Rahul Oad, Ali Irtaza Sayani, Shadi Banitaan:
Predicting Severity of US Traffic Accidents: A Machine Learning Approach. EIT 2024: 679-685 - 2023
- [j12]Mingzuoyang Chen, Shadi Banitaan, Mina Maleki:
Enhancing Pedestrian Group Detection and Tracking Through Zone-Based Clustering. IEEE Access 11: 132162-132179 (2023) - [j11]Ziba Parsons, Shadi Banitaan:
Commentary on Automatic identification of Chagas disease vectors using data mining and deep learning techniques. Ecol. Informatics 75: 102064 (2023) - [c29]Yichun Li, Mina Maleki, Shadi Banitaan, Mingzuoyang Chen:
State of Health Estimation of Lithium-ion Batteries Using Convolutional Neural Network with Impedance Nyquist Plots. ICPRAM 2023: 842-849 - 2022
- [c28]Hebah Alquran, Shadi Banitaan:
Fake News Detection in Social Networks Using Data Mining Techniques. AIIoT 2022: 155-160 - [c27]Mingzuoyang Chen, Shadi Banitaan, Mina Maleki, Yichun Li:
Pedestrian Group Detection with K-Means and DBSCAN Clustering Methods. EIT 2022: 1-6 - [c26]Yichun Li, Mina Maleki, Shadi Banitaan, Mingzuoyang Chen:
State of Health Indicator Modeling of Lithium-ion Batteries Using Machine Learning Techniques. EIT 2022: 440-445 - [c25]Bassam A. Abdelghani, Sophia Fadal, Shadi Bedoor, Shadi Banitaan:
Prediction of Heart Attacks using Data Mining Techniques. ICMLA 2022: 951-956 - [c24]Mingzuoyang Chen, Shadi Banitaan, Mina Maleki, Yichun Li:
GDSCAN: Pedestrian Group Detection using Dynamic Epsilon. ICMLA 2022: 1748-1753 - [c23]Bassam A. Abdelghani, Mina Maleki, Shadi Banitaan, Amna Mazen:
Occupancy Detection based on WI-FI SysLog Data. ICMLA 2022: 1754-1760 - [c22]Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan:
On Selection of Optimal Kernel Function for Software Defect Prediction. ICMLA 2022: 1761-1768 - 2021
- [j10]Bassam A. Abdelghani, Shadi Banitaan, Mina Maleki, Amna Mazen:
Kissing Bugs Identification Using Convolutional Neural Network. IEEE Access 9: 140539-140548 (2021) - [j9]Zeinab Parsons, Shadi Banitaan:
Automatic identification of Chagas disease vectors using data mining and deep learning techniques. Ecol. Informatics 62: 101270 (2021) - [c21]Yichun Li, Mina Maleki, Shadi Banitaan, Mingzuoyang Chen:
Data-Driven State of Charge Estimation of Li-ion Batteries using Supervised Machine Learning Methods. ICMLA 2021: 873-878 - 2020
- [j8]Cuauhtémoc López Martín, Yenny Villuendas-Rey, Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan:
Transformed k-nearest neighborhood output distance minimization for predicting the defect density of software projects. J. Syst. Softw. 167: 110592 (2020) - [c20]Ghaith Al-Refai, Mohammed Al-Refai, Shadi Banitaan, Zeinab Ghasemi:
Shared Images in A Connected-Vehicle Network Registration System Using Harris-Stephens Approach. EIT 2020: 47-52 - [c19]Jordan Yono, Antonio Segura, Yongqiang Sun, Shadi Banitaan:
Machine Learning Techniques to Evaluate Whether Twitter Accounts Are Human or Robot. EIT 2020: 304-308 - [c18]Zeinab Ghasemi, Shadi Banitaan, Ghaith Al-Refai:
Automated Chagas Disease Vectors Identification using Data Mining Techniques. EIT 2020: 540-545
2010 – 2019
- 2019
- [c17]Mohammed Akour, Shadi Banitaan, Hiba Alsghaier, Khalid Al Radaideh:
Predicting Daily Activities Effectiveness Using Base-level and Meta level Classifiers. ISDFS 2019: 1-7 - [i4]Cuauhtémoc López Martín, Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan:
v-SVR Polynomial Kernel for Predicting the Defect Density in New Software Projects. CoRR abs/1901.03362 (2019) - 2018
- [j7]Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan:
Comparative analysis of soft computing techniques for predicting software effort based use case points. IET Softw. 12(1): 19-29 (2018) - [c16]Cuauhtémoc López Martín, Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan:
Upsilon-SVR Polynomial Kernel for Predicting the Defect Density in New Software Projects. ICMLA 2018: 1377-1382 - [c15]Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan, Cuauhtémoc López Martín:
Ensemble of Learning Project Productivity in Software Effort Based on Use Case Points. ICMLA 2018: 1427-1431 - [i3]Mamdouh Alenezi, Shadi Banitaan, Mohammad Zarour:
Using Categorical Features in Mining Bug Tracking Systems to Assign Bug Reports. CoRR abs/1804.07803 (2018) - [i2]Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan, Cuauhtémoc López Martín:
Ensemble of Learning Project Productivity in Software Effort Based on Use Case Points. CoRR abs/1812.06459 (2018) - 2017
- [j6]Shadi Banitaan, Kendall E. Nygard, Kenneth Magel:
Test Focus Selection for Integration Testing. Int. J. Softw. Eng. Knowl. Eng. 27(8): 1145-1166 (2017) - [j5]Heba Al-Quraan, Emad Abu-Shanab, Shadi Banitaan, Heyam Al-Tarawneh:
Motivations for using social media: comparative study based on cultural differences between American and Jordanian students. Int. J. Soc. Media Interact. Learn. Environ. 5(1): 48-61 (2017) - [c14]Ali Bou Nassif, Mohammad Azzeh, Shadi Banitaan:
Robust Rank Aggregation method for Case-Base effort estimation. CCECE 2017: 1-5 - [c13]Cuauhtémoc López Martín, Shadi Banitaan, Andrés García-Floriano, Cornelio Yáñez-Márquez:
Support Vector Regression for Predicting the Enhancement Duration of Software Projects. ICMLA 2017: 562-567 - [i1]Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan, Fadi Almasalha:
Pareto Efficient Multi Objective Optimization for Local Tuning of Analogy Based Estimation. CoRR abs/1701.01675 (2017) - 2016
- [j4]Iyad Alazzam, Mohammed Akour, Shadi Banitaan, Feras Hanandeh:
Feature-Based Test Focus Selection Technique Using Classes Connections Weight. Int. J. Oper. Res. Inf. Syst. 7(1): 33-44 (2016) - [j3]Ali Bou Nassif, Mohammad Azzeh, Shadi Banitaan, Daniel Neagu:
Guest editorial: special issue on predictive analytics using machine learning. Neural Comput. Appl. 27(8): 2153-2155 (2016) - [j2]Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan, Fadi Almasalha:
Pareto efficient multi-objective optimization for local tuning of analogy-based estimation. Neural Comput. Appl. 27(8): 2241-2265 (2016) - [c12]Shadi Banitaan, Mohammad Azzeh, Ali Bou Nassif:
User Movement Prediction: The Contribution of Machine Learning Techniques. ICMLA 2016: 571-575 - 2015
- [c11]Shadi Banitaan, Ali Bou Nassif, Mohammad Azzeh:
Class Decomposition Using K-Means and Hierarchical Clustering. ICMLA 2015: 1263-1267 - [c10]Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan:
An Application of Classification and Class Decomposition to Use Case Point Estimation Method. ICMLA 2015: 1268-1271 - 2014
- [c9]Ali Bou Nassif, Shadi Banitaan:
A Better Case Adaptation Method for Case-Based Effort Estimation Using Multi-objective Optimization. ICMLA 2014: 409-414 - 2013
- [j1]Mamdouh Alenezi, Kenneth Magel, Shadi Banitaan:
Efficient Bug Triaging Using Text Mining. J. Softw. 8(9): 2185-2190 (2013) - [c8]Shadi Banitaan, Mamdouh Alenezi:
TRAM: An approach for assigning bug reports using their Metadata. ICCIT 2013: 215-219 - [c7]Shadi Banitaan, Mamdouh Alenezi:
DECOBA: Utilizing Developers Communities in Bug Assignment. ICMLA (2) 2013: 66-71 - [c6]Mamdouh Alenezi, Shadi Banitaan:
Bug Reports Prioritization: Which Features and Classifier to Use? ICMLA (2) 2013: 112-116 - [c5]Shadi Banitaan, Mamdouh Alenezi, Kendall E. Nygard, Kenneth Magel:
Towards Test Focus Selection for Integration Testing Using Method Level Software Metrics. ITNG 2013: 343-348 - 2011
- [c4]Saeed Salem, Loqmane Seridi, Rami Alroobi, James E. Brewer, Shadi Banitaan, Ibrahim Aljarah:
CLARM: an integrative approach for functional modules discovery. BCB 2011: 646-650 - [c3]Saeed Salem, Shadi Banitaan, Ibrahim Aljarah, James E. Brewer, Rami Alroobi:
Discovering Communities in Social Networks Using Topology and Attributes. ICMLA (1) 2011: 40-43 - [c2]Ibrahim Aljarah, Shadi Banitaan, Sameer Abufardeh, Wei Jin, Saeed Salem:
Selecting discriminating terms for bug assignment: a formal analysis. PROMISE 2011: 12 - 2010
- [c1]Shadi Banitaan, Saeed Salem, Wei Jin, Ibrahim Aljarah:
A formal study of classification techniques on entity discovery and their application to opinion mining. SMUC@CIKM 2010: 29-36
Coauthor Index
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