CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children حسب Jayakanth Kunhoth (14158908)

"…Three machine learning algorithms support vector machine (SVM), AdaBoost, and Random forest are employed to assess the performance of the CNN features and fused CNN features. …"

Artificial Intelligence in Predicting Cardiac Arrest: Scoping Review حسب Asma Alamgir (18288895)

"…Machine learning models were the most prominent branch of AI used in the prediction of cardiac arrest in the studies (38/47, 81%), and the most used algorithm was the neural network (23/47, 49%). …"

Edge intelligence for network intrusion prevention in IoT ecosystem حسب Mansura, Habiba

"…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …"
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A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method حسب Shahid Rahman (16904613)

"…Every communication body wants to secure their data while communicating over the Internet. The internet has various benefits but the main demerit is the privacy and security and the transmission of data over insecure network or channel may happen. …"

A novel few shot learning derived architecture for long-term HbA1c prediction حسب Marwa Qaraqe (10135172)

"…Short-term CGM time-series data are processed using both novel image transformation approaches, as well as using conventional signal processing methods. …"

Building power consumption datasets: Survey, taxonomy and future directions حسب Yassine Himeur (14158821)

"…The latter will be very useful for testing and training anomaly detection algorithms, and hence reducing wasted energy. Moving forward, a set of recommendations is derived to improve datasets collection, such as the adoption of multi-modal data collection, smart Internet of things data collection, low-cost hardware platforms and privacy and security mechanisms. …"

Synthesis with VHDL. (c2001) حسب Halawi, Hatem

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Adaptive Federated Learning Architecture To Mitigate Non-IID Through Multi-Objective GA-Based Efficient Client Selection حسب Ajaj, Mohamad

"…Federated Learning (FL) has emerged as a promising framework for collaborative model training across distributed devices without centralizing sensitive data. …"
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A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks حسب Sakib Mahmud (15302404)

"…Deep reinforcement learning (DRL) offers a data-driven alternative that couples perception with sequential decision-making. …"

Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis حسب Sami Elzeiny (16891521)

Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study حسب Muhammad Atif Butt (10849980)

"…Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. …"

Edge intelligence for network intrusion prevention in IoT ecosystem حسب Mansura Habiba (17808302)

"…This paper proposes a deep learning-based algorithm to protect the network against Distributed Denial-of-Service (DDoS) attacks, insecure data flow, and similar network intrusions. …"

Generation and Detection of Sign Language Deepfakes - A Linguistic and Visual Analysis حسب Naeem, Shahzeb

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Precision nutrition: A systematic literature review حسب Daniel Kirk (17302798)

"…As such, recent research has applied machine learning algorithms, tools, and techniques in precision nutrition for different purposes. …"

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins حسب Samir Brahim, Belhaouari

"…ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …"
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE حسب Ben Romdhane, Haifa

"…., dry and bare soil. SAR data were complemented with very high-resolution Worldview-3 multispectral images (0.31 m panchromatic, 1.24 m VNIR) to obtain a visual assessment of the study area and its land cover features. …"
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE حسب Ben-Romdhane, Haïfa

"…., dry and bare soil. SAR data were complemented with very high-resolution Worldview-3 multispectral images (0.31 m panchromatic, 1.24 m VNIR) to obtain a visual assessment of the study area and its land cover features. …"
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Developing an online hate classifier for multiple social media platforms حسب Joni Salminen (7434770)

"…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …"

Using artificial intelligence to improve body iron quantification: A scoping review حسب Abdulqadir J. Nashwan (11659453)

"…A systematic search was performed to identify studies that utilize machine learning in iron-related disorders. The search revealed a wide range of machine learning algorithms used by different studies. …"

Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method حسب Mohamed Massaoudi (16888710)

"…This paper addresses the high volatility of PV power by proposing a precise and reliable ensemble learning model for short-term PV power generation forecasting. …"