Advanced metaheuristic optimization techniques in applications of deep neural networks: a review
Deep neural networks (DNNs) have evolved as a beneficial machine learning method that
has been successfully used in various applications. Currently, DNN is a superior technique …
has been successfully used in various applications. Currently, DNN is a superior technique …
A review on community detection in large complex networks from conventional to deep learning methods: A call for the use of parallel meta-heuristic algorithms
Complex networks (CNs) have gained much attention in recent years due to their
importance and popularity. The rapid growth in the size of CNs leads to more difficulties in …
importance and popularity. The rapid growth in the size of CNs leads to more difficulties in …
Hybrid models based on genetic algorithm and deep learning algorithms for nutritional Anemia disease classification
S Kilicarslan, M Celik, Ş Sahin - Biomedical Signal Processing and Control, 2021 - Elsevier
Deep learning algorithms are an important part of disease prediction and diagnosis by
analyzing health data. If not diagnosed and treated early, symptoms of nutritional anemia …
analyzing health data. If not diagnosed and treated early, symptoms of nutritional anemia …
A hybrid CNN-GLCM classifier for detection and grade classification of brain tumor
A Gurunathan, B Krishnan - Brain Imaging and Behavior, 2022 - Springer
A supervised CNN Deep net classifier is proposed for the detection, classification and
diagnosis of meningioma brain tumor using deep learning approach. This proposed method …
diagnosis of meningioma brain tumor using deep learning approach. This proposed method …
A survey of designing convolutional neural network using evolutionary algorithms
Convolutional neural networks (CNN) are highly effective for image classification and
computer vision activities. The accuracy of CNN architecture depends on the design and …
computer vision activities. The accuracy of CNN architecture depends on the design and …
Detection and diagnosis of brain tumors using deep learning convolutional neural networks
A Gurunathan, B Krishnan - International Journal of Imaging …, 2021 - Wiley Online Library
The detection of brain tumors in brain magnetic resonance imaging (MRI) image is an
important process for preventing earlier death. This article proposes an automated computer …
important process for preventing earlier death. This article proposes an automated computer …
A framework of genetic algorithm-based CNN on multi-access edge computing for automated detection of COVID-19
This paper designs and develops a computational intelligence-based framework using
convolutional neural network (CNN) and genetic algorithm (GA) to detect COVID-19 cases …
convolutional neural network (CNN) and genetic algorithm (GA) to detect COVID-19 cases …
Enhancing solar photovoltaic modules quality assurance through convolutional neural network-aided automated defect detection
Detecting cracks in solar photovoltaic (PV) modules plays an important role in ensuring their
performance and reliability. The development of convolutional neural networks (CNNs) has …
performance and reliability. The development of convolutional neural networks (CNNs) has …
Mbfquant: a multiplier-bitwidth-fixed, mixed-precision quantization method for mobile cnn-based applications
P Peng, M You, K Jiang, Y Lian… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Deploying Convolutional Neural Network (CNN)-based applications to mobile platforms can
be challenging due to the conflict between the restricted computing capacity of mobile …
be challenging due to the conflict between the restricted computing capacity of mobile …
A zeroth-order adaptive learning rate method to reduce cost of hyperparameter tuning for deep learning
Y Li, X Ren, F Zhao, S Yang - Applied Sciences, 2021 - mdpi.com
Due to powerful data representation ability, deep learning has dramatically improved the
state-of-the-art in many practical applications. However, the utility highly depends on fine …
state-of-the-art in many practical applications. However, the utility highly depends on fine …