A Convection Nowcasting Method Based on Machine Learning by Aifang Su, Han Li, Liman Cui, Yungang Chen

“…The test analysis demonstrated that the algorithm combined the image feature extraction ability of the convolutional neural network (CNN) and the sequential learning ability of the long short-term memory network (LSTM) model to establish an end-to-end deep learning network, which could deeply extract high-order features of radar echoes such as structural texture, spatial correlation, and temporal evolution compared with the traditional algorithm. …”
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Narrative analysis of media coverage of Philippines’s tourism policies during the Covid-19 pandemic (2020-2021) by Dickyizmi Syahputra, Dyah Mutiarin

“…For the purpose of this study, examples were drawn from various news articles published on CNN Philippines, Inquirer.net, and pna.gov.ph that covered the years 2020 and 2021. …”
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Deep generative modeling of annotated bacterial biofilm images by Angelina A. Holicheva, Konstantin S. Kozlov, Daniil A. Boiko, Maxim S. Kamanin, Daria V. Provotorova, Nikita I. Kolomoets, Valentine P. Ananikov

“…Synthetic datasets can significantly improve the training of computer vision models for automated biofilm analysis, as demonstrated with the application of Mask R-CNN detection model. The approach represents a key advance in the field of biofilm research, offering a scalable solution for generating high-quality training data and working with different strains of microorganisms at different stages of formation. …”
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Diplomatik Kriz Dönemlerinde Medyanın Ritmi: Skripal ve Kaşıkçı Olayları Üzerine Karşılaştırmalı Ritimanaliz by Canan Eyigün

“…Bu çalışmada diplomatik krizlerinmedyanın ritmini nasıl etkilediği ve haber ritmi üzerinden krizlerin nasıl devam ettirildiği gösterilmeyeçalışılmıştır. BBC, CNN ve RT’nin Skripal olayı ve Kaşıkçı suikastına dair haberleri Henri Lefebvretarafından temelleri atılan “ritimanaliz” yöntemiyle incelenmiştir. …”
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Recent advances in journal bearings: wear fault diagnostics, condition monitoring and fault diagnosis methodologies by Nazik Jebur, Wafa Soud

“…Key findings indicate that ensemble models, such as the CNN and deep neural network (CNNEPDNN) model, significantly improve convergence speed, test accuracy, and F-Score in bearing fault diagnosis by 15-20% compared to individual models. …”
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Masked and Unmasked Face Recognition Model Using Deep Learning Techniques. A case of Black Race. by Mabirizi, Vicent, Ampaire, Ray Brooks, Muhoza, Gloria B.

“…Machine learning techniques such as Principal Component Analysis, Geometric Feature Based Methods and double threshold techniques were used in the development phase while results were classified using CNN pre-trained models. From results obtained, VGG19 achieved the higher accuracy of 91.2% followed by Inception V 3 at 90.3% and VGG16 with 89.69% whereas the developed model achieved 90.32%.…”
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Masked and unmasked Face Recognition Model Using Deep Learning Techniques. A case of Black Race. by Mabiriz,I, Vicent, Ampaire, Ray Brooks, Muhoza, B. Gloria

“…Machine learning techniques such as Principal Component Analysis, Geometric Feature-Based Methods, and double threshold techniques were used in the development phase while results were classified using CNN pre-trained models. From the results obtained, VGG19 achieved a higher accuracy of 91.2% followed by Inception V 3 at 90.3% and VGG16 at 89.69% whereas the developed model achieved 90.32%.…”
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End-to-End Information Extraction from Courier Order Images Using a Neural Network Model with Feature Enhancement by Wei Shen, Han Li, Youbo Jin, Chase Q. Wu

“…We constructed our feature enhancement module, Co-G-Ma, based on a convolutional neural network (CNN), gated recurrent unit (GRU), and multi-head attention. …”
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A Robust Multi-Modal Deep Learning-Based Fault Diagnosis Method for PV Systems by Shahabodin Afrasiabi, Sarah Allahmoradi, Mousa Afrasiabi, Xiaodong Liang, C. Y. Chung, Jamshid Aghaei

“…The results indicate that the proposed model outperforms conventional CNN- and MSVM-based methods, demonstrating its potential in providing precise fault diagnostics in PV systems.…”
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Implementasi Algoritma Convolutional Neural Network untuk Klasifikasi Jenis Keris by Maria Mediatrix Sebatubun, Cosmas Haryawan

“…Penelitian ini akan mengimplementasikan metode deep learning dengan algoritma Convolutional Neural Network (CNN) yang dapat melakukan tugas klasifikasi secara langsung pada citra, untuk membangun sebuah model untuk klasifikasi jenis keris berdasarkan dhapur. …”
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Application of deconvolutional networks for feature interpretability in epilepsy detection by Sihao Shao, Yu Zhou, Ruiheng Wu, Aiping Yang, Qiang Li

“…The Fully Convolutional Network (FCN) can provide the model’s interpretability but has not been applied in seizure detection.MethodsTo address these challenges, a novel convolutional neural network (CNN) model, combining SE (Squeeze-and-Excitation) modules, was proposed on top of the FCN. …”
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A Dual-Path Neural Network for High-Impedance Fault Detection by Keqing Ning, Lin Ye, Wei Song, Wei Guo, Guanyuan Li, Xiang Yin, Mingze Zhang

“…Our dual-branch network simultaneously processes both representations: the CNN extracts spatial features from the transformed images, while the GRU captures temporal features from the raw signals. …”
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CoLR: Classification-Oriented Local Representation for Image Recognition by Tan Guo, Lei Zhang, Xiaoheng Tan, Liu Yang, Zhiwei Guo, Fupeng Wei

“…Specifically, the deep features of the object dataset are obtained by a well-trained convolutional neural network (CNN) with five convolutional layers and three fully connected layers on the challenging ImageNet. …”
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Multimodal Data Fusion for Depression Detection Approach by Mariia Nykoniuk, Oleh Basystiuk, Nataliya Shakhovska, Nataliia Melnykova

“…These networks were developed using convolutional neural network (CNN) layers to learn local patterns, a bidirectional LSTM (Bi-LSTM) to process sequences, and a self-attention mechanism to improve focus on key parts of the data. …”
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Physical Model versus Artificial Neural Network (ANN) Model: A Comparative Study on Modeling Car-Following Behavior at Signalized Intersections by Lan Yang, Shan Fang, Guoyuan Wu, He Sheng, Zhigang Xu, Mengxiao Zhang, Xiangmo Zhao

“…In this study, two novel Artificial Neural Network (ANN) CF models, the Convolutional Neural Network—Long Short-term Memory (CNN-LSTM) and the Convolution-LSTM (Conv-LSTM)—are first applied to predict CF behaviors at signalized intersections. …”
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Using deep learning model integration to build a smart railway traffic safety monitoring system by Chin-Chieh Chang, Kai-Hsiang Huang, Tsz-Kin Lau, Chung-Fah Huang, Chun-Hsiung Wang

“…Therefore, this study aimed to build a smart railway traffic safety system using the integration of object detection, segmentation, machine learning, and notification system. First, the Mask R-CNN model was applied to automatically build the digital boundaries of railway, which achieved an average Interest of Union (IOU) of over 0.9. …”
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Gesture-controlled reconfigurable metasurface system based on surface electromyography for real-time electromagnetic wave manipulation by Chen Junzai, Li Weiran, Gong Kailuo, Lu Xiaojie, Tong Mei Song, Wang Xiaoyi, Yang Guo-Min

“…By recognizing the sEMG signals of user gestures through a pre-trained convolutional neural network (CNN) model, the system dynamically modulates the metasurface, enabling precise control of the deflection direction and polarization state of electromagnetic waves. …”
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Adaptive Image Denoising Method Based on Diffusion Equation and Deep Learning by Shaobin Ma, Lan Li, Chengwen Zhang

“…A neural network is used to realize image denoising because of its good learning ability of image statistical characteristics, mainly by the diffusion equation and deep learning (CNN) algorithm as the foundation, focus on the effects of activation function of network optimization, using multiple feature extraction technology in-depth networks to study the characteristics of the input image richer, and how to better use the adaptive algorithm on the depth of diffusion equation and optimization backpropagation learning. …”
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Optimalisasi Hyper Parameter Convolutional Neural Networks Menggunakan Ant Colony Optimization by Fian Yulio Santoso, Eko Sediyono, Hindriyanto Dwi Purnomo

“…Salah satu metode tersebut menggabungkan convolutional neural networks (CNN) dengan deep learning, tetapi hyperparameter, seperti fungsi loss, fungsi aktivasi, dan optimizers, memengaruhi kinerjanya. …”
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YOLOSeg with applications to wafer die particle defect segmentation by Yen-Ting Li, Yu-Cheng Chan, Chen-Che Huang, Yu-Chang Hsu, Ssu-Han Chen

“…Even when the sizes of particle defects are extremely small, the performance of YOLOSeg is far superior to current instance segmentation models such as mask R-CNN, YOLACT, YUSEG, and Ultralytics’s YOLOv5s-segmentation. …”
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