Feature fusion based on joint sparse representations and wavelets for multiview classification by Younes Akbari (14150781)

“…Generally, a dataset can be created in different views, features, or modalities. To improve the classification rate, local information is shared among different views by various fusion methods. …”

Lung cancer medical images classification using hybrid CNN-SVM by Abdulrazak Yahya Saleh (18520026)

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Stress Classification Using Photoplethysmogram-Based Spatial and Frequency Domain Images by Sami Elzeiny (16891521)

“…Three types of classification models were built: person-specific models, generic classification models, and calibrated-generic classification models. …”

An Exemplar Pyramid Feature Extraction Based Alzheimer Disease Classification Method by Heba Soliman Zaina (16904787)

“…In term of binary-class classification, we were able to achieve very good results using both GM and WM. …”

Cancerous and Non-Cancerous MRI Classification Using Dual DCNN Approach by Zubair Saeed (19325647)

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Hybrid Neural Networks for Precise Hydronephrosis Classification Using Deep Learning by Abdus Salam (1918387)

“…The framework also supported hydronephrosis classification using the fluid-to-kidney area ratio, with a threshold of 0.213 derived from prior literature. …”

Construction Materials Classification Using Wi-Fi and Convolutional Neural Networks by Gacem, Mohamed Ait

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Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning by Kaddoura, Yara

“…A Master of Science thesis in Computer Engineering by Yara Kaddoura entitled, “Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning”, submitted in January 2023. …”
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Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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FPGA-based Parallel Hardware Architecture for Real-time Object Classification by Qasaimeh, Murad Mohammad

“…A Master of Science thesis in Computer Engineering by Murad Mohammad Qasaimeh entitled, "FPGA-based Parallel Hardware Architecture for Real-time Object Classification," submitted in June 2014. Thesis advisor is Dr. …”
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LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications by Aldamani, Raghad

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Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System by Abougharib, Arwa

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Advancing crop classification in smallholder agriculture: A multifaceted approach combining frequency-domain image co-registration, transformer-based parcel segmentation, and Bi-LSTM for crop classification by Waleed Khan (9427344)

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Surface Modification of Poly(lactic acid) Film via Cold Plasma Assisted Grafting of Fumaric and Ascorbic Acid by Asma Abdulkareem (14634508)

Exploring cyclodextrin-driven advancements in aqueous Zn-ion battery: A review by Ahmed Hazem Abdelhay (20487281)

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PD-L1 Expression in Human Breast Cancer Stem Cells Is Epigenetically Regulated through Posttranslational Histone Modifications by Pramod Darvin (153341)

“…Moreover, an overexpression of histone acetylation enzymes was observed in tumorspheres suggesting the active involvement of histone modifications in EMT-induced PD-L1 expression. In summary, EMT-associated overexpression of PD-L1 was partially independent of promoter CpG methylation and more likely to be dependent on posttranslational histone modifications. …”

تعديل السلوك التعبدي في السنة النبوية by Al-Sharifeen, Emad Abdullah

Subjects: “…Behavior modification…”
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Modelling of Asphalt’s Adhesive Behaviour Using Classification and Regression Tree (CART) Analysis by Md Arifuzzaman (11471123)

“…<p>The modification by polymers and nanomaterials can significantly improve different properties of asphalt. …”

CLASSIFICATION OF REFACTORING METHODS FOR ASPECT ORIENTED PROGRAMMING BASED ON SOFTWARE QUALITY ATTRIBUTES by Al-Jamimi, Hamdi Ali

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Kernel-Ridge-Regression-Based Randomized Network for Brain Age Classification and Estimation by Raveendra Pilli (21633287)

“…Features from MRI images are extracted using 3-D-CNN and fed into the wavelet KRR-RVFL network for brain age classification and prediction. The proposed algorithm achieved high classification accuracy, 97.22%, 99.31%, and 95.83% for GM, WM, and CSF regions, respectively. …”