A Survey of Audio Enhancement Algorithms for Music, Speech, Bioacoustics, Biomedical, Industrial, and Environmental Sounds by Image U-Net by Sania Gul (18272227)

“…We will discuss the need for AE, U-Net comparison to other DNNs, the benefits of converting the audio to 2D, input representations that are useful for different AE applications, the architecture of vanilla U-Net and the pre-trained models, variations in vanilla architecture incorporated in different E models, and the state-of-the-art AE algorithms based on U-Net in various applications. …”

Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data by Rajesh Kumar Dhanaraj (19646269)

Content-Symmetrical Multidimensional Transpose of Image Sequences for the High Efficiency Video Coding (HEVC) All-Intra Configuration by Shanableh, Tamer

“…This work proposes a pre- and post-coding solution using the content-symmetrical multidimensional transpose of raw video sequences. …”
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Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

Pre-production movie rating prediction using machine learning. (c2017) by Gerges, Firas Abdallah

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A kernelization algorithm for d-Hitting Set by Abu-Khzam, Faisal N.

“…For a given parameterized problem, π, a kernelization algorithm is a polynomial-time pre-processing procedure that transforms an arbitrary instance of π into an equivalent one whose size depends only on the input parameter(s). …”
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Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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Fetal ECG Signal Enhancement by Ahmadi, Maryam

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Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

“…This study compresses the generative pre-trained transformer (GPT) by 65%, saving time and memory without causing performance loss. …”

Cortical EEG Source Localization of Focal Epilepsy by Siyam, Wisal Elfatih Mohamed

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Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study by Alaa Abd-alrazaq (17058018)

“…</p><h3>Objective</h3><p dir="ltr">In this paper, we propose a machine learning–based approach for identifying research gaps through the analysis of scientific literature. …”

Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis by Hassan Ali (3348749)

“…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”

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

“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Segmenting Handwritten Arabic Text by Haraty, Ramzi A.

“…The algorithm then generates pre-segmentation points for these blocks. …”
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A Neuro-Heuristic Approach for Segmenting Handwritten Arabic Text by Haraty, Ramzi

“…The algorithm then generates pre-segmentation points for these blocks. …”
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Salak Image Classification Method Based Deep Learning Technique Using Two Transfer Learning Models by Theng, Lau Wei

“…The dataset consists of 1000 images which having 250 of images for each type of salak. Pre-processing on the dataset is required to standardize the dataset by resizing the image into 224 * 224 pixels, convert into jpg format and augmentation. …”
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A neuro-heuristic approach for segmenting handwritten Arabic text. (c2001) by Hamid, Alaa A.

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

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A novel hybrid methodology for fault diagnosis of wind energy conversion systems by Khaled Dhibi (16891524)

“…The proposed technique involved two major steps: feature selection and fault classification. Feature selection pre-processing is an important step to increase the accuracy of the classification algorithm and decrease the dimensionality of a dataset. …”