An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm by Ghulam Jillani Ansari (16896342)

“…The Support Vector Machine (SVM) algorithm is used for classification and the average F-Score is used as fitness function and target condition. …”

Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)

Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala (22330876)

“…Our model achieved an average classification accuracy of 97.25 percent, exceeding current leading techniques. …”

FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

“…The proposed design achieves an average throughput of 163.24 Gbps, exceeding throughputs of reported hardware-based classifiers that use comparable approaches, which in turn ensures the continuity of realtime traffic classification at congested data centers.…”
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FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

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

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LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications by Aldamani, Raghad

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

“…Our reported results have shown promising classification accuracy with an average of 92.35%. This sheds some light on the feasibility of automating the classification of a morphologically complex language text (Arabic). …”
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DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ResultMost traditional machine learning algorithms achieved distinction accuracies of over 99 percent, whereas DeepRaman demonstrated an exceptional accuracy of 100 percent. …”
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Forecasting the Direction of GCC Stock Indexes Using Support Vector Machine (SVM) Algorithm by Zeino, Yaser Abdullah

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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

“…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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PILE-UP FREE PARAMETER ESTIMATION AND DIGITAL ONLINE PEAK LOCALIZATION ALGORITHMS FOR GAMMA RAY SPECTROSCOPY by Noras, J.M.

“…The classification technique has the unique feature of cutting down the computation largely by only allowing the event of interest to be executed by a particular algorithm. …”
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A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm by Amirsajjad Rahmani (17541453)

“…The proposed model accurately predicted critical machining conditions for unbalanced datasets. The classification model indicates an average recall, precision, and accuracy of 80%, 86%, and 95%, respectively, when predicting workpiece quality and tool breakage.…”

Gesture-based Graph-theoretic Robot Formation Control by Sajid, Mahroo

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Wavelet Analysis- Singular Value Decomposition Based Method for Precise Fault Localization in Power Distribution Networks Using k-NN Classifier by Abhishek Raj (7245425)

“…The results demonstrate a high fault classification accuracy of 99.08%, with an average localization error of just 1.2% of the total line length. …”

Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques by Hassan, Mahitab Alaaeldin

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A Novel Fault Diagnosis of Uncertain Systems Based on Interval Gaussian Process Regression: Application to Wind Energy Conversion Systems by Majdi Mansouri (16869885)

“…In the proposed IGPR-RF technique, the effective interval-valued nonlinear statistical features are extracted and selected using the IGPR model and then fed to the RF algorithm for fault classification purposes. The proposed technique is characterized by a better handling of WEC system uncertainties such as wind variability, noise, measurement errors, which leads to an improved fault classification accuracy. …”

DNA Base-Calling Techniques by Odeh, Fadi

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Defining quantitative rules for identifying influential researchers: Insights from mathematics domain by Ghulam Mustafa (458105)

“…The rules were developed for each parameter category using the Decision Tree Algorithm, which achieved an average accuracy of 70 to 75 percent for identifying awardees in mathematics domains. …”

The Assessment and Allocation of Public Private Partnership Risks in the UAE by Shaban, Mazhd

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