Convolution of the physical point cloud for predicting the self-assembly of colloidal particles by Seunghoon Kang, Young Jin Lee, Kyung Hyun Ahn

“…The phases predicted by our model are not limited to liquid-like dispersions and solid–liquid phase separations, where thermodynamic equilibrium differs, but also include sample-spanning gel structures, where only kinetics differ while thermodynamics remain the same. …”
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Enhancing Remote Sensing Image Resolution Using Convolutional Neural Networks by Julian Supardi, Samsuryadi Samsuryadi, Hadipurnawan Satria, Philip Alger M. Serrano, Arnelawati Arnelawati

“…Remote sensing images differ from ordinary images taken with conventional cameras. …”
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Detection Of Vacant Parking Spaces Through The Use Of Convolutional Neural Network by Christopher Singh, Christoforos Christoforou

“…This paper focuses on the application of computer vision and convolutional neural network techniques in the automotive industry to reduce the amount of time required to locate a vacant parking spot and to reduce driving time. …”
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Fault Diagnosis for Imbalanced Datasets Based on Deep Convolution Fuzzy System by Junwei Zhu, Linfang Zhu

“…To address the data imbalance issue in the process of collecting bearing fault data in industrial environments and to enhance the robustness and generalization ability of fault diagnosis, this paper proposes a bearing fault diagnosis method based on a Bidirectional Autoregressive Variational Autoencoder (BAVAE) and a Deep Convolutional Interval Type-2 Fuzzy System (DCIT2FS). …”
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Dynamic Range Expansion Using Cumulative Histogram Learning for High Dynamic Range Image Generation by Hanbyol Jang, Kihun Bang, Jinseong Jang, Dosik Hwang

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3D-CNN detection of systemic symptoms induced by different Potexvirus infections in four Nicotiana benthamiana genotypes using leaf hyperspectral imaging by Rizos-Theodoros Chadoulis, Ioannis Livieratos, Ioannis Manakos, Theodore Spanos, Zeinab Marouni, Christos Kalogeropoulos, Constantine Kotropoulos

“…In this study, the use of 3D Convolutional Neural Networks (3D-CNNs) was explored to detect presymptomatic viral infections in the model plant Nicotiana benthamiana L. and assess the generalization of these models across different plant genotypes. …”
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Highway Traffic Flow Prediction Algorithm Based on Multiscale Transformation and Convolutional Networks by Yuzhu Luo, Jiarong Wang, Ming Wei

“…In order to solve the problem that the traditional long-term high-speed traffic forecasting algorithm is affected by the approximation ability of the function and easy to fall into the local mass value, we wrote a multivariate-based highway traffic forecasting algorithm scaling and convolutional networks. Because the feedforward wavelet neural network algorithm predicts the short-term traffic flow in different areas, it is necessary to examine the ability to predict the difference between different models. …”
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IPACN: Information-Preserving Adaptive Convolutional Network for Remote Sensing Change Detection by Hongchao Qi, Xin Gao, Jiaqiang Lei, Fenglei Wang

“…Crucially, IPACN incorporates a Frequency-Adaptive Difference Enhancement Module (FADEM) that applies adaptive filtering, informed by frequency analysis concepts, directly to the bi-temporal difference features. …”
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Acoustic emission localization model of concrete material based on convolutional neural network by DENG Yongdong, ZHOU Jingren, LU Xiang, CHEN Jiangkang

“…In this paper, a convolutional neural network-based acoustic emission localization model is constructed by taking the cylindrical concrete specimen as the experimental object, taking the 3D coordinates of eight sensors and the propagation time difference as input, and the 3D coordinate position of the acoustic emission source as output. …”
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Reservoir Stochastic Simulation Based on Octave Convolution and Multistage Generative Adversarial Network by Xuechao Wu, Wenyao Fan, Shijie Peng, Bing Qin, Qing Wang, Mingjie Li, Yang Li

“…Specifically, a pyramid structure is introduced to perform multiscale representation based on single Training Image (TI), with feature information being captured under different scales. Then, the octave convolution is used to perform multi-frequency feature representation on different feature maps. …”
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Deep spatio-temporal dependent convolutional LSTM network for traffic flow prediction by Jie Tang, Rong Zhu, Fengyun Wu, Xuansen He, Jing Huang, Xianlai Zhou, Yishuai Sun

“…In this paper, we design a space-dependent attention mechanism, which assigns a convolutional neural network with a different kernel size to each region through attention weights. …”
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Criminal emotion detection framework using convolutional neural network for public safety by Jay Raval, Nilesh Kumar Jadav, Sudeep Tanwar, Giovanni Pau, Fayez Alqahtani, Amr Tolba

“…Once the crime is detected, criminal faces are extracted using the region of interest and stored in a directory. Different CNN architectures, such as LeNet-5, VGGNet, RestNet-50, and basic CNN, are used to detect different emotions of the face. …”
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AFMF: adaptive fusion of multi-hop neighborhood features in graph convolutional network by Kang Liu, Xinyu Li, Lian Liu, Zhihao Xv, Aohang Pei, Runshi Ji

“…However, heterophilic graphs where adjacent nodes may belong to different categories are ubiquitous and cannot be directly processed by GNNs. …”
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Model Predictive Control Algorithm for Converter Based on a Convolutional Neural Network by Kun Shen, Mengyao Wu, Rongbin Chen

“…To address this issue, this article designs a switching strategy for neural network controller model parameters of converters and employs a convolutional neural network (CNN) to identify the converter load type. …”
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Fusion of Geochemical Data and Remote Sensing Data Based on Convolutional Neural Network by Shi Bai, Jie Zhao, Tianhan Yu, Yunqing Shao

“…And transfer learning is applied to the fusion of different elements. Ag and Cr are selected to verify the mobility and generalization of the model. …”
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Through-Wall Radar Classification of Human Posture Using Convolutional Neural Networks by Alper Kılıç, İsmail Babaoğlu, Ahmet Babalık, Ahmet Arslan

“…On the other hand, the success of classification with deep learning methods in different problems is remarkable. Since the radar signals contain valuable information about the objects behind the wall, the use of deep learning techniques for classification purposes will give a different direction to the research. …”
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Research on basketball footwork recognition based on a convolutional neural network algorithm by Weili Bao, Yong Bai

“…Objective: The purpose of this paper is to utilize a convolutional neural network (CNN) to identify the types of basketball footwork of athletes as a way to assist in the training of basketball players' footwork and to improve their performance in the game. …”
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A Dual-channel Progressive Graph Convolutional Network via subgraph sampling by Wenrui Guan, Xun Wang

“…Graph Convolutional Networks (GCNs) demonstrate an excellent performance in node classification tasks by updating node representation via aggregating information from the neighbor nodes. …”
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Arsitektur Convolutional Neural Network untuk Model Klasifikasi Citra Batik Yogyakarta by Arya Prayoga, Maimunah, Pristi Sukmasetya, Muhammad Resa Arif Yudianto, Rofi Abul Hasani

“…The recognition of Yogyakarta batik motifs can utilize technology to classify images of Yogyakarta batik motifs based on patterns using the Convolutional Neural Network (CNN). The Yogyakarta batik motif images used for classification totaled 600 images consisting of 3 different motifs such as ceplok, kawung, and parang. …”
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Convolutional Neural Networks to Facilitate the Continuous Recognition of Arabic Speech with Independent Speakers by Sally A. Sayed, Rania Ahmed Abdel Azeem Abul Seoud, Howida Y. Abdel Naby

“…The first uses a combination of convolutional neural network (CNN) and long short-term memory (LSTM) encoders, and an attention-based decoder, and the second is based on the Sphinx-4 recognizer, which includes pocket sphinx, base sphinx, and sphinx train, with various types and number of features to be extracted (filter bank and mel frequency cepstral coefficients (MFCC)) based on the CMU Sphinx tool, which generates a language model for different sentences spoken by different speakers. …”
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