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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Deep Convolutional Generative Adversarial Network and Convolutional Neural Network for Smoke Detection by Hang Yin, Yurong Wei, Hedan Liu, Shuangyin Liu, Chuanyun Liu, Yacui Gao

“…Besides, we designed an improved convolutional neural network (CNN) model for extracting smoke features and smoke detection. …”
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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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A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks by Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar

“…In this line, this work fuses multi-source data—satellite imagery, weather data, and soil properties—through the approach of multi-modal fusion using Convolutional Neural Networks and Recurrent Neural Networks. …”
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Classification of Computer Network Users with Convolutional Neural Networks by Jakub Nowak, Marcin Korytkowski, Rafał Scherer

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Enhancing geometric modeling in convolutional neural networks: limit deformable convolution by Wei Wang, Yuanze Meng, Han Li, Guiyong Chang, Shun Li, Chenghong Zhang

“…Abstract Convolutional neural networks (CNNs) are constrained in their capacity to model geometric transformations due to their fixed geometric structure. …”
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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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Convolution Smooth: A Post-Training Quantization Method for Convolutional Neural Networks by Yongyuan Chen, Zhendao Wang

Subjects: “…Convolutional neural network…”
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Tensor Network Methods for Hyperparameter Optimization and Compression of Convolutional Neural Networks by A. Naumov, A. Melnikov, M. Perelshtein, Ar. Melnikov, V. Abronin, F. Oksanichenko

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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

“…This research presents a comprehensive study of an ensemble convolutional recurrent neural network (CRNN) model designed for sound event detection (SED) in residential and public safety contexts. …”
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Automatic Image Colorization Based on Convolutional Neural Networks by L. V. Serebryanaya, V. V. Potaraev

Subjects: “…artificial neural network…”
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Multi-Input Convolutional Neural Network for Flower Grading by Yu Sun, Lin Zhu, Guan Wang, Fang Zhao

“…A new dataset named BjfuGloxinia contains three quality grades; each grade consists of 107 samples and 321 images. A multi-input convolutional neural network is designed for large scale flower grading. …”
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