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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…This work proposes various machine learning methods, including transfer learning via fine-tuning, transfer learning via feature extraction, ensembles of deep convolutional neural network (CNN) models, and fusion of CNN features, to develop a preliminary dysgraphia diagnosis system based on handwritten images. …”
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163
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…This work proposes various machine learning methods, including transfer learning via fine-tuning, transfer learning via feature extraction, ensembles of deep convolutional neural network (CNN) models, and fusion of CNN features, to develop a preliminary dysgraphia diagnosis system based on handwritten images. …”
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164
Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022“…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …”
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165
Combinatorial method for bandwidth selection in wind speed kernel density estimation
Published 2019“…In this study, a non-parametric combinatorial method is implemented for obtaining an accurate non-parametric kernel density estimation (KDE)-based statistical model of wind speed, in which the selection of the bandwidth parameter is optimised concerning mean integrated absolute error (L 1 error ) between the true and hypothesised densities. …”
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166
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167
Incorporation of Robust Sliding Mode Control and Adaptive Multi-Layer Neural Network-Based Observer for Unmanned Aerial Vehicles
Published 2024“…<p dir="ltr">The control and state estimation of Unmanned Aerial Vehicles (UAVs) provide significant challenges due to their complex and nonlinear dynamics, as well as uncertainties arising from factors such as sensor noise, wind gusts, and parameter fluctuations. Neural network-based methods tackle these problems by accurately approximating unknown nonlinearities through training on input-output data. …”
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168
Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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169
A method for optimizing test bus assignment and sizing for system-on-a-chip
Published 2017“…Test access mechanism (TAM) is an important element of test access architectures for embedded cores and is responsible for on-chip test patterns transport from the source to the core under test to the sink. …”
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conferenceObject -
170
Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem
Published 1999“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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171
Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem
Published 2023“…In particular, a new modified method based on the Arithmetic Optimization Algorithm is proposed. …”
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172
A Modular Reconfigurable Architecture for Asymmetric and Symmetric-key Cryptographic Algorithms
Published 2007“…Numerous such algorithms have been devised, and many have found popularity in different domains. …”
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173
A method for efficient NoC test scheduling using deterministic routing
Published 2017“…The method uses a deterministic routing algorithm that minimizes test time while avoiding blocking. …”
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conferenceObject -
174
Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images
Published 2023“…The leading mathematical arithmetic operators' distributional nature is used by the AOA method. The picture histogram was used to construct the candidate solutions in the modified algorithms, which were then updated according to the algorithm's features. …”
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175
A simplified sliding‐mode control method for multi‐level transformerless DVR
Published 2022“…<p dir="ltr">Here, a finite-control-set sliding-mode control (FCS-SMC) method is proposed for single-phase three-level T-type inverter-based transformerless dynamic voltage restorers (TDVRs). …”
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176
Evolutionary Game-Based Battery Scheduling: A Comparative Study for Prosumers in Smart Grids
Published 2025“…A comprehensive comparative analysis is conducted between the proposed EGT algorithm and established methods such as centralized optimization (CO), game theory (GT), and auction-based approaches. …”
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177
Novel Peak Detection Algorithms for Pileup Minimization in Gamma Ray Spectroscopy
Published 2006“…A number of parameter estimation and digital online peak localisation algorithms are being developed, including a pulse classification technique which uses a simple peak search routine based on the smoothed first derivative method, which gave a percentage error of peak amplitude of less than 1%. …”
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178
Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier
Published 2023“…The preprocessed images are segmented with hybrid Fuzzy C Means (FCM) and Gaussian Mixture Model (GMM) which partition the image into sub groups to make it easier for classification by reducing the complexity. …”
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179
A family of minimum curvature variable-methods for unconstrained optimization. (c1998)
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masterThesis -
180