An Improved Convolutional Neural Networks: Quantum Pseudo-Transposed Convolutional Neural Networks by Li Hai, Chen Liang, Hao Yaming, Yu Wenli, Shi Fengquan

Subjects: “…Convolutional neural networks…”
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Optimizing Convolutional Neural Network Architectures by Luis Balderas, Miguel Lastra, José M. Benítez

Subjects: “…convolutional neural network simplification…”
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Convolutional neural network for IT lung diagnostics by U. A. Vishniakou, T. He

“…The structure of a convolutional neural network (CNN), which was trained on a standard dataset of respiratory diseases, is given. …”
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Multiscale Convolutional Neural Networks for Hand Detection by Shiyang Yan, Yizhang Xia, Jeremy S. Smith, Wenjin Lu, Bailing Zhang

“…Deep learning models, and deep convolutional neural networks (CNNs) in particular, have achieved state-of-the-art performances in many vision benchmarks. …”
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Water Classification Using Convolutional Neural Network by Saira Asghar, Ghulam Gilanie, Mubbashar Saddique, Hafeez Ullah, Heba G. Mohamed, Irshad Ahmed Abbasi, Mohamed Abbas

“…The enhanced image samples were then fed to the proposed Convolutional Neural Network (CNN)-based model named WaterNet (WNet) for classification. …”
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Computing nasalance with MFCCs and Convolutional Neural Networks. by Andrés Lozano, Enrique Nava, María Dolores García Méndez, Ignacio Moreno-Torres

“…A new approach is proposed to compute nasalance using Convolutional Neural Networks (CNNs) trained with Mel-Frequency Cepstrum Coefficients (mfccNasalance). mfccNasalance is evaluated by examining its accuracy: 1) when the train and test data are from the same or from different dialects; 2) with test data that differs in dynamicity (e.g. rapidly produced diadochokinetic syllables versus short words); and 3) using multiple CNN configurations (i.e. kernel shape and use of 1 × 1 pointwise convolution). …”
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Voice Detection Using Convolutional Neural Network by U. A. Vishniakou, B. H. Shaya

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Combining Convolutional Neural Networks for Fungi Classification by Anuruk Prommakhot, Jakkree Srinonchat

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Tailoring convolutional neural networks for custom botanical data by Jamie R. Sykes, Katherine J. Denby, Daniel W. Franks

“…Methods We address this gap with informed data collection and the development of a new convolutional neural network architecture, PhytNet. Utilising a novel dataset of infrared cocoa tree images, we demonstrate PhytNet's development and compare its performance with existing architectures. …”
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CNNFET: Convolutional neural network feature Extraction Tools by Huseyin Atasoy, Yakup Kutlu

Subjects: “…Convolutional neural networks…”
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Convolutional Neural Networks for Predicting Power Outages in Baghdad by Saja Jafar Jawad, Shaymaa. W. Al-Shammari

“…The research uses this dataset to train one-dimensional Convolutional Neural Networks (1D CNN) to find patterns and relationships that can accurately predict when power outages can happen in the long term and short term to improve the management of the Baghdad electricity grid through data-driven networks. …”
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An Ensemble of Convolutional Neural Networks for Sound Event Detection by Abdinabi Mukhamadiyev, Ilyos Khujayarov, Dilorom Nabieva, Jinsoo Cho

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Automatic Image Colorization Based on Convolutional Neural Networks by L. V. Serebryanaya, V. V. Potaraev

“…Classifier is based on using convolutional neural network, and colorizer is based on hash table which stores mapping of hypercolumns and colors. …”
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Multi-Input Convolutional Neural Network for Flower Grading by Yu Sun, Lin Zhu, Guan Wang, Fang Zhao

“…A multi-input convolutional neural network is designed for large scale flower grading. …”
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Flood Image Classification using Convolutional Neural Networks by Olusogo Julius Adetunji, Ibrahim Adepoju Adeyanju, Adebimpe Omolayo Esan, Adedayo Aladejobi Sobowale Sobowale

Subjects: “…Convolutional neural networks…”
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Quantized convolutional neural networks: a hardware perspective by Li Zhang, Olga Krestinskaya, Mohammed E. Fouda, Ahmed M. Eltawil, Khaled Nabil Salama

Subjects: “…convolutional neural networks…”
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Using Convolutional Neural Networks for segmentation of brain tumors by Kauã Gabriel Silva de Lima, Vagner Alves Ferreira da Silva, João Victor Oliveira da Silva, Lucas Patrick Ramos de Oliveira, Diogo Lopes da Silva

“… This paper presents a brain tumor segmentation system for MRI images using Convolutional Neural Networks (CNNs). The goal is to assist in automated medical analysis by providing accurate segmentations of tumor areas to support diagnosis and treatment planning. …”
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Dog Activity Recognition Using Convolutional Neural Network by Evenizer Nolasco, Anton Caesar Aldea, Jocelyn Villaverde

“…To create a new model, we used convolutional neural networks (CNNs) on a Raspberry Pi platform and the InceptionV3 model, optimized on a dataset of Siberian Husky photos. …”
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Malaria Disease Prediction Based on Convolutional Neural Networks by Dhrgam AL Kafaf, Noor N. Thamir, Samara S. AL-Hadithy

Subjects: “…Convolutional Neural Network…”
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Classification of Computer Network Users with Convolutional Neural Networks by Jakub Nowak, Marcin Korytkowski, Rafał Scherer

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