Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

“…A Master of Science thesis in Ccomputer Engineering by Muhammad Arbab Arshad entitled, “Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data”, submitted in August 2021. …”
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Breast Density Estimation in Mammograms Using Unsupervised Image Segmentation by Alhusari, Khaldoon

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Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges by Muhammad Usama (3629090)

“…Recently, there has been a rising trend of employing unsupervised machine learning using unstructured raw network data to improve network performance and provide services, such as traffic engineering, anomaly detection, Internet traffic classification, and quality of service optimization. …”

Target Detection Using Learning Methods by Sahnoon, Mohammad Moufeed

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InShaDe: Invariant Shape Descriptors for visual 2D and 3D cellular and nuclear shape analysis and classification by Khaled Al-Thelaya (17302711)

“…We demonstrate the capabilities of our framework in the context of visual analysis and unsupervised classification of 2D histology images and 3D nuclear envelopes extracted from serial section electron microscopy stacks.…”

Application of Data Mining to Predict and Diagnose Diabetic Retinopathy by Haniyeh, Maryam

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Multi Self-Organizing Map (SOM) Pipeline Architecture for Multi-View Clustering by Saadia Jamil (22045946)

“…A self-organizing map is one of the well-known unsupervised neural network algorithms used for preserving typologies during mapping from the input space (high-dimensional) to the display (low-dimensional).An algorithm called Local Adaptive Receptive Field Dimension Selective Self-Organizing Map 2 is a modified form of a self-organizing Map to cater different data types in the dataset. …”

The Use of Supply Chain Metrics in Lebanon by Huballah, Zeina

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Use of Data Mining Techniques to Detect Fraud in Procurement Sector by AL HAMMADI, SUMAYYA ABDULLA

“…This research aims to analyze the reliability and efficiency of data mining techniques in detecting and preventing fraud in the procurement sector in the UAE and globally. The method used in this research is a classification of models and algorithms used in data mining. …”
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A spectral-ensemble deep random vector functional link network for passive brain–computer interface by Ruilin Li (5627456)

“…However, automatically decoding raw <u>electroencephalogram</u> (EEG) data using RNNs is still challenging in EEG-based passive brain–computer interface (pBCI) <u>classification tasks</u>. …”

An Efficient Brain Tumor Segmentation Method Based on Adaptive Moving Self-Organizing Map and Fuzzy K-Mean Clustering by Surjeet Dalal (4906894)

“…The tumor images were separated from non-tumor images using the AMSOM classification approach. At last, the FKM was used to distinguish the tumor region from the surrounding tissue. …”

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis by Hassan, Ali

“…This work introduces a novel, unsupervised detection methodology for detecting adversarial inputs to NLP classifiers. …”
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Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…This work introduces a novel, unsupervised detection methodology for detecting adversarial inputs to NLP classifiers. …”

A Machine Learning Approach to Predicting Diabetes Complications by Jian, Yazan Khaled

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Genome‐wide DNA methylation analysis of colorectal adenomas with and without recurrence reveals an association between cytosine‐phosphate‐guanine methylation and histological subty... by David Fiedler (2672563)

“…Unsupervised hierarchical clustering exhibited a significant association of methylation patterns with histological adenoma subtypes. …”