Modulation recognition method based on multiscale convolutional fusion coding networks by LI Guojun, ZHU Siyuan, ZHENG Jianzhong, WANG Jie, YE Changrong

“…Experimental results demonstrated the model's robust stability and generalization capability, showing minimal performance variation under different test batch sizes with fixed training batches. …”
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Crop classification with deep convolutional neural network based on crop feature by Mohamad Reza Gili, Davoud Ashourloo, Hosein Aghighi, Ali Akbar Matkan, Alireza SHakiba

“…Then the algorithm was implemented using these feature channels in the test area and the overall accuracy was upgraded to 86% and the kappa coefficient to 0.82 compared to which indicated a significant improvement in the results compared to the previous case.Conclusion:The deep convolutional neural network is very sensitive to the type of input channels for detecting agricultural crops and selecting the channels with suitable tempo-spectral characteristics for different types of crops, has a great impact on the accuracy of network training and can reduce the loss of training network and increase its efficiency in the classification of various crops.…”
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Deep Convolutional Neural Networks in Medical Image Analysis: A Review by Ibomoiye Domor Mienye, Theo G. Swart, George Obaido, Matt Jordan, Philip Ilono

“…Deep convolutional neural networks (CNNs) have revolutionized medical image analysis by enabling the automated learning of hierarchical features from complex medical imaging datasets. …”
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Image Recognition Based on Multiscale Pooling Deep Convolution Neural Networks by Haitao Sang, Li Xiang, Shifeng Chen, Bo Chen, Li Yan

“…To achieve this, through making full use of block information of different sizes and scales in the image, a multiscale pooling deep convolution neural network model is designed in this paper. …”
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Klasifikasi Penyakit Pneumonia menggunakan Metode Convolutional Neural Network (CNN) by irfan office

“…With automatic classification technology, pneumonia detection becomes more efficient. The study used Convolutional Neural Network (CNN) with ResNet50 architecture to classify types of pneumonia, including viral pneumony and COVID-19, from chest x-rays. …”
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A point cloud segmentation network with hybrid convolution and differential channels by Xiaoyan Zhang, Yantao Bu

“…For this reason, we propose a 3D segmentation network based on hybrid convolution and differential channels. Specifically, we design a hybrid convolutional feature extraction (HCFE) module for processing 3D semantic information and spatial information independently, using different convolution kernels to obtain the subtle geometric structure differences between points. …”
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Dynamic Hypergraph Convolutional Networks for Hand Motion Gesture Sequence Recognition by Dong-Xing Jing, Kui Huang, Shi-Jian Liu, Zheng Zou, Chih-Yu Hsu

“…The T-Module, a multiscale temporal convolution module, aggregates features from multiple frames to capture gesture dynamics across different time scales. …”
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FOV Expansion of Bioinspired Multiband Polarimetric Imagers With Convolutional Neural Networks by Yongqiang Zhao, Miaomiao Wang, Guang Yang, Jonathan Cheung-Wai Chan

“…In order to overcome the limits, this paper presents a deep learning method for FOV expansion, incorporating the gradient prior of the image into a nine-dimensional convolutional neural network's framework to learn end-to-end mapping between the incomplete images and the FOV-expanded images. …”
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Deep Communication: Exploring End-to-End Wireless with Convolutional Neural Network by Sumaira Mushtaq, Bahman R Alyaeia, Momna Sultan, Janshair Khan

“…In this paper, we propose a new approach to achieving end-to-end wireless communication using convolutional neural networks (CNNs) in the presence of Nakagami fading, Additive white Gaussian noise (AWGN), and multiple-input multiple-output (MIMO) fading channels. …”
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Triple Graph Convolutional Network for Hyperspectral Image Feature Fusion and Classification by Maryam Imani, Daniele Cerra

“…These graphs are processed using graph convolutional networks, and their results are fused using a cross-attention mechanism. …”
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Runx1 mediates the development of the granular convoluted tubules in the submandibular glands. by Hitomi Ono Minagi, Safiye Esra Sarper, Hiroshi Kurosaka, Koh-Ichi Kuremoto, Ichiro Taniuchi, Takayoshi Sakai, Takashi Yamashiro

“…The mouse granular convoluted tubules (GCTs), which are only located in the submandibular gland (SMG) are known to develop and maintain their structure in an androgen-dependent manner. …”
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UHVDC Transmission Fault Location Based on Residual Convolutional Neural Network by LI Ji, ZHANG Xueyou, ZHANG Junjie, SHI Wen, RUAN Wei, DAI Jianfeng

“…Firstly, wavelet transform is used to extract fault voltage and current of different frequency bands, which are used as input of residual convolution neural network. …”
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Convolutional neural network–based person tracking using overhead views by Misbah Ahmad, Imran Ahmed, Fakhri Alam Khan, Fawad Qayum, Hanan Aljuaid

“…The advancement of convolutional neural network reforms the way of object tracking. …”
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Packaging Design Image Segmentation Based on Improved Full Convolutional Networks by Chunxiao Zhang, Mengmeng Han, Jingjing Jia, Chulsoo Kim

“…This study draws inspiration from advanced NLP techniques and proposes an improved fully convolutional network (FCN) model for image semantic segmentation, which is applied to packaging design. …”
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Computer-aided cholelithiasis diagnosis using explainable convolutional neural network by Dheeraj Kumar, Mayuri A. Mehta, Ketan Kotecha, Ambarish Kulkarni

“…Although several computer-aided cholelithiasis diagnosis approaches have been introduced in the literature, their use is limited because Convolutional Neural Network (CNN) models are black box in nature. …”
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Spatiotemporal analysis of mangroves using median composites and convolutional neural network by Kathiroli R, Madhumitha P S, Achyut Prasad D C, Sandhiya S

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Graph-informed convolutional autoencoder to classify brain responses during sleep by Sahar Zakeri, Somayeh Makouei, Sebelan Danishvar

“…We designed a graph-informed convolutional autoencoder called GICA to extract high-level features from the functional connectivity features. …”
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Fingerprint recognition using convolution neural network with inversion and augmented techniques by Reena Garg, Gunjan Singh, Aditya Singh, Manu Pratap Singh

“…The simulation results have been obtained with different optimizers and it has been observed that VGG 19 model exhibits the accuracies of 88 % and 93 % with inversion and multi augmentation approaches respectively. …”
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Comparative convolutional neural networks for perovskite solar cell PCE predictions by Milan Harth, D. Kishore Kumar, Said Kassou, Kenza El Idrissi, Ritesh Kant Gupta, Yonatan Daniel, Ofry Makdasi, Iris Visoly-Fisher, Alessio Gagliardi

“…This study presents a deep learning methodology that correlates optical reflective images of perovskite solar cells with their PCE by focusing on image differences rather than absolute visual features. The approach predicts relative changes in PCE by comparing images of the same device in different states (e.g., before and after encapsulation) or against a reference image. …”
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Detection of human activities using multi-layer convolutional neural network by Essam Abdellatef, Rasha M. Al-Makhlasawy, Wafaa A. Shalaby

“…The HARCNN model is designed with 10 convolutional blocks, referred to as “ConvBlk.” Each block integrates a convolutional layer, a ReLU activation function, and a batch normalization layer. …”
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