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

Subjects: “…Coding theory…”
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Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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A neural networks algorithm for data path synthesis by Harmanani, Haidar M.

“…The algorithm is driven by a motion equation that determines the neurons firing conditions based on the modified Hopfield neural network model of computation. …”
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem by Harmanani, Haidar M.

“…In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs† by Harmanani, Haidar

“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …”
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”

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

“…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …”

Detecting COVID-19 From Lung Computed Tomography Images: A Swarm Optimized Artificial Neural Network Approach by S. Punitha (17945654)

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Variable Selection in Data Analysis: A Synthetic Data Toolkit by Mitra, Rohan

“…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …”
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A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

“…The evaluation criteria used in the algorithms of different neural network types and how they play a large role in the highly accurate classification of Arabic texts are discussed. …”
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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid (22047578)

Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

“…<p>Code completion serves as a fundamental aspect of modern software development, improving developers' coding processes. …”

NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES by Al-Garni, Ahmed Z.

“…., Boeing 737, is analyzed using the Artificial Neural Network and Weibull regression models. One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are used for the analysis. …”
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Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units by Shanableh, Tamer

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Modelling Exchange Rates during Currency Crisis using Neural Networks by Nasr, G. E.

“…The models are built using the feedforward ANN structure trained by the backpropagation algorithm. …”
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Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System by Abu Zitar, Raed

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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

A decentralized load balancing strategy for parallel search-three optimization. (c2010) by Mouawad, Amer E.

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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”

How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation by Joni Salminen (7434770)