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201
Exploring new horizons in neuroscience disease detection through innovative visual signal analysis
Published 2024“…Electroencephalogram (EEG) analysis is crucial for diagnosing brain disorders, but it can be challenging for medical practitioners to interpret complex EEG signals and make accurate diagnoses. To address this, our study focuses on visualizing complex EEG signals in a format easily understandable by medical professionals and deep learning algorithms. …”
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202
Scatter search technique for exam timetabling
Published 2011“…This approach is based on maintaining and evolving a population of solutions. …”
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203
LDSVM: Leukemia Cancer Classification Using Machine Learning
Published 2022“…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …”
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204
Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging
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206
Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study
Published 2023“…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. …”
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207
An efficient cache replacement strategy for the hybrid cache consistency approach
Published 2010“…Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. …”
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A fine-grained XML structural comparison approach
Published 2007“…Our approach consists of two main algorithms for discovering the structural commonality between sub-trees and computing tree-based edit operations costs. …”
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210
FarmTech: Regulating the use of digital technologies in the agricultural sector
Published 2023“…<p dir="ltr">Farming relies on the accurate collection and processing of data. Algorithms utilizing artificial intelligence can predict patterns and spot problems, helping farmers make more informed decisions. …”
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211
Cohen syndrome and early-onset epileptic encephalopathy in male triplets: two disease-causing mutations in VPS13B and NAPB
Published 2023“…Sanger sequencing verified the segregation of the two recessive gene variants with the phenotype in family members. The prediction algorithms support the pathogenicity of these variants. …”
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212
An XML Document Comparison Framework
Published 2001“…Most of them make use of techniques for finding the edit distance between tree structures, XML documents being modeled as Ordered Labeled Trees. …”
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213
Enhancing e-learning through AI: advanced techniques for optimizing student performance
Published 2024“…AI algorithms, known for their cognitive ability and capacity to learn, adapt, and make decisions, are employed to analyze and forecast student performance, thereby improving educational quality and outcomes. …”
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214
Deepfakes Signatures Detection in the Handcrafted Features Space
Published 2023“…In the Handwritten Signature Verification (HSV) literature, several synthetic databases have been developed for data-augmentation purposes, where new specimens and new identities were generated using bio-inspired algorithms, neuromotor synthesizers, Generative Adversarial Networks (GANs) as well as several deep learning methods. …”
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215
Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases
Published 2024“…These AI algorithms are effective non-invasive biomarkers for cardiovascular illnesses because they can identify subtle patterns and signals in the ECG that may not be readily apparent to human interpreters. …”
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216
Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Many efforts have been deployed by the IR community to extend freetext query processing toward semi-structured XML search. Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. …”
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