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processing algorithm » processing algorithms (Expand Search)
could algorithm » mould algorithm (Expand Search), carlo algorithm (Expand Search), colony algorithm (Expand Search)
element » elements (Expand Search)
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101
Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
Published 2022“…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. …”
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102
A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems
Published 2025“…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. …”
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103
Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare
Published 2007“…Since even segmenting the log into clusters may not solve the problem, as clusters/segments may grow to be humongous in size, this is in case of high data/transaction dependency, we suggest a method for segmenting the log into clusters and its sub-clusters; i.e, segmenting the cluster; based on exact data dependency [12], into sub-clusters; based on two different criteria: number of data items or space occupied. …”
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104
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…Moreover, the study proposes a hybrid algorithm that combines UniBFS with two filter-based FS methods, ReliefF and Fisher, to identify pertinent features during the global search phase. …”
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106
Sentiment analysis for Arabizi in social media. (c2015)
Published 2015“…Yalla 7abibi, it is very useful to have a data mining tool that can analyze the sentiment of Twitter users in the Arab world. …”
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masterThesis -
107
Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…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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108
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109
Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms
Published 2022“…While the previous studies mostly used ANN to demonstrate the capability of MLs to predict PG over the mechanistic or correlation-based models, the present research has shown that GP is even better than ANN using a wide range of FPs and a large data set.…”
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111
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113
Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE
Published 2018“…Educational Data Mining (EDM) is the process of discovering information and relationships from educational data for better understanding of students’ performance, and characteristics of their education providers. …”
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114
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115
Test Vector Decomposition Based Static Compaction Algorithms for Combinational Circuits
Published 2003“…In addition, two new TVD based static compaction algorithms are presented. …”
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116
Multi-marker-LD based genetic algorithm for tag SNP selection
Published 2014“…The performance of the three algorithms are compared with those of a recognized tag SNP selection algorithm using three different real data sets from the HapMap project. …”
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117
Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units
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118
Parallel processing
Published 2005“…Parallel algorithms, based on simulated annealing, neural networks and genetic algorithms, for mapping irregular data to multicomputers are presented and compared. …”
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conferenceObject -
119
Parallel implementation of clique partitioning using artificial neural networks. (c2000)
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masterThesis -
120
Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”