Навчання моделей згорткових нейронних мереж виявленню об’єктів, сцен і контекстів на зображеннях... by Роман Орлов, Сергій Таборанський

“…Дослідження присвячене розробці оптимізованої згорткової нейронної мережі (CNN) для виявлення об'єктів, сцен та контекстів у різноманітних зображеннях. …”
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Crack Identification Method of Steel Fiber Reinforced Concrete Based on Deep Learning: A Comparative Study and Shared Crack Database by Yang Ding, Shuang-Xi Zhou, Hai-Qiang Yuan, Yuan Pan, Jing-Liang Dong, Zhong-Ping Wang, Tong-Lin Yang, An-Ming She

“…Finally, a concrete crack identification model based on YOLOv4 and Mask R-CNN is established. In addition, the improved Mask R-CNN method is proposed in order to improve the prediction accuracy based on the Mask R-CNN. …”
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The Short-Term Wind Power Forecasting by Utilizing Machine Learning and Hybrid Deep Learning Frameworks by Sunku V.S., Namboodiri V., Mukkamala R.

“…In pursuit of these objectives, the CNN GRU model was rigorously tested and compared against three additional models: CNN with bidirectional long short-term memory (BiLSTM), extreme gradient boosting (XGBoost), and random forest (RF). …”
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Enhanced streamflow forecasting using hybrid modelling integrating glacio-hydrological outputs, deep learning and wavelet transformation by Jamal Hassan Ougahi, John S Rowan

“…Hybrid models (CNN-LSTM1 to CNN-LSTM15) were trained using meteorological data augmented with glacio-hydrological model outputs representing ice and snow-melt contributions to streamflow. …”
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Lithium-Ion Battery State of Health Degradation Prediction Using Deep Learning Approaches by Talal Alharbi, Muhammad Umair, Abdulelah Alharbi

“…Three deep learning architectures 1D Convolutional Neural Networks (CNN), CNN plus Long Short-Term Memory (LSTM), and CNN plus Gated Recurrent Units (GRU) are used in the centralized approach. …”
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License Plate Detection with Shallow and Deep CNNs in Complex Environments by Li Zou, Meng Zhao, Zhengzhong Gao, Maoyong Cao, Huarong Jia, Mingtao Pei

“…To address these two conflicting challenges, we propose to detect license plate based on two CNNs, a shallow CNN and a deep CNN. The shallow CNN is used to quickly remove most of the background regions to reduce the computation cost, and the deep CNN is used to detect license plate in the remaining regions. …”
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Integrated Machine Learning Approaches for Landslide Susceptibility Mapping Along the Pakistan–China Karakoram Highway by Mohib Ullah, Haijun Qiu, Wenchao Huangfu, Dongdong Yang, Yingdong Wei, Bingzhe Tang

“…To address this, this study assessed the performance of six machine learning models, including Convolutional Neural Networks (CNNs), Random Forest (RF), Categorical Boosting (CatBoost), their CNN-based hybrid models (CNN+RF and CNN+CatBoost), and a Stacking Ensemble (SE) combining CNN, RF, and CatBoost in mapping landslide susceptibility along the Karakoram Highway in northern Pakistan. …”
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A Classroom Emotion Recognition Model Based on a Convolutional Neural Network Speech Emotion Algorithm by Qinying Yuan

“…The network used in this paper is a combination of convolutional neural network (CNN) and recurrent neural network (RNN), which takes advantage of both CNN for feature extraction and RNN for memory capability in the sequence model. …”
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An efficient loop tiling framework for convolutional neural network inference accelerators by Hongmin Huang, Xianghong Hu, Xueming Li, Xiaoming Xiong

“…Given the highly parallel workloads of the CNN, a CNN accelerator with a 14 × 16 processing element array is designed in this study to accelerate the CNN inference. …”
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Cross-ViT based benign and malignant classification of pulmonary nodules. by Qinfang Zhu, Liangyan Fei

“…There are many methods using Convolutional neural network (CNN) for benign and malignant classification of pulmonary nodules, but traditional CNN models focus more on the local features of pulmonary nodules and lack the extraction of global features of pulmonary nodules. …”
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Improving person re-identification based on two-stage training of convolutional neural networks and augmentation by S. A. Ihnatsyeva, R. P. Bohush

“…A technology for two-stage training of convolutional neural networks (CNN) is presented, characterized by the use of image augmentation for the preliminary stage and fine tuning of weight coefficients based on the original images set for training. …”
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Automatic Evaluation of Internal Combustion Engine Noise Based on an Auditory Model by Kai Liang, Haijun Zhao

“…The results showed that the sound quality evaluation model based on the CNN could predict the sound quality of internal combustion engines more accurately, and the input evaluation score based on the auditory spectrum in the CNN classification model was more accurate than the short-time average energy input evaluation score based on the time domain.…”
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ZleepNet: A Deep Convolutional Neural Network Model for Predicting Sleep Apnea Using SpO2 Signal by Hnin Thiri Chaw, Thossaporn Kamolphiwong, Sinchai Kamolphiwong, Krongthong Tawaranurak, Rattachai Wongtanawijit

“…In this paper, we propose a deep convolutional neural network (CNN) model based on the oxygen saturation (SpO2) signal from a smart sensor. …”
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Urdu Lip Reading Systems for Digits in Controlled and Uncontrolled Environment by Amanullah Baloch, Mushtaq Ali, Lal Hussain, Touseef Sadiq, Badr S. Alkahtani

“…To address these issues, we contribute by introducing the ULRD dataset, employing diverse data augmentation techniques, and comparing three DNN models: a Hybrid 2D-3D CNN-LSTM model, a LipNet-based 2D CNN-LSTM model, and a baseline 3D CNN-GRU model. …”
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Analysis and Risk Assessment of Corporate Financial Leverage Using Mobile Payment in the Era of Digital Technology in a Complex Environment by Wenjing Wei, Bingxiang Li

“…Combined with a single-layer neural network or CNN model, the comparison experiment is carried out in two ways. …”
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Perbandingan Arsitektur Convolutional Neural Network Pada Klasifikasi Pneumonia, COVID-19, Lung Opacity, dan Normal Menggunakan Citra Sinar-X Thoraks by Agung Wahyu Setiawan

“…Sebagai tambahan, studi ini juga membandingkan kinerja dua pengoptimasi, yaitu Adam dan SGD untuk masing-masing arsitektur CNN. Kinerja tertinggi diperoleh dengan menggunakan arsitektur CNN berbasis ResNet50v1 dan pengoptimasi Adam dengan nilai rerata akurasi pelatihan, validasi, dan pengujian mencapai 92,22 ± 0,25 %.   …”
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Klasifikasi Ekspresi Wajah Menggunakan Covolutional Neural Network by Ahmad Taufiq Akbar, Shoffan Saifullah, Hari Prapcoyo

“…Penelitian ini mengusulkan arsitektur sederhana Convolutional Neural Network (CNN) untuk meningkatkan efisiensi klasifikasi emosi pada dataset kecil. …”
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Denoising and deconvolving CT images of unknown origin: comparing linear Wiener-deconvolution with deep convolutional neural network Noise2Inverse by Simon Zabler, Antoine Klos, Pierre Lhuissier, Luc Salvo, Maziyar Farahmandi, Simon Wittl

“…The Noise2Inverse framework allows for training these CNN using a split-and-merge of two subsets generated from one raw CT dataset. …”
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Convolutional Neural Network-Based Fish Posture Classification by Xin Li, Anzi Ding, Shaojie Mei, Wenjin Wu, Wenguang Hou

“…The first is a paired binary classification CNN and the second is a four-category CNN. In addition, three kinds of CNN are adopted. …”
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Enhancing lane detection in autonomous vehicles with multi-armed bandit ensemble learning by J. Arun Pandian, Ramkumar Thirunavukarasu, L. Thanga Mariappan

“…The results overcome the performance of the individual CNN models and state-of-the-art ensemble techniques. …”
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