A Gaussian Process-Enhanced Non-Linear Function and Bayesian Convolution–Bayesian Long Term Short Memory Based Ultra-Wideband Range Error Mitigation Method for Line of Sight and No... by A. S. M. Sharifuzzaman Sagar, Samsil Arefin, Eesun Moon, Md Masud Pervez Prince, L. Minh Dang, Amir Haider, Hyung Seok Kim

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Lung volume assessment for mean dark-field coefficient calculation using different determination methods by Florian T. Gassert, Jule Heuchert, Rafael Schick, Henriette Bast, Theresa Urban, Tina Dorosti, Gregor S. Zimmermann, Sebastian Ziegelmayer, Alexander W. Marka, Markus Graf, Marcus R. Makowski, Daniela Pfeiffer, Franz Pfeiffer

“…Abstract Background Accurate lung volume determination is crucial for reliable dark-field imaging. We compared different approaches for the determination of lung volume in mean dark-field coefficient calculation. …”
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Effects of different wearable sensors and locomotion tasks on machine learning-based joint moment prediction by Jonas Weber, Bernd J. Stetter

“…Simultaneously acquired motion capture and wearable sensor data (unilaterally positioned on the right foot, thigh, shank, as well as on the torso) from 21 participants performing stair ascent and descent, ramp ascent and descent, and treadmill walking were used (Camargo et al., 2021). Convolutional neural networks (CNNs) were trained on three different inputs combining all locomotion tasks: 1. a dataset from four IMUs, 2. a dataset from eleven EMG sensors, and 3. a dataset from both sensors (the IMUs and EMG sensors). …”
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Circular Slot Antenna with Pattern Diversity by Youngje Sung

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RACNet: risk assessment Net of cervical lesions in colposcopic images by Tianxiang Xu, Peizhong Liu, Ping Li, Xiaoxia Wang, Huifeng Xue, JingMing Guo, Binhua Dong, Pengming Sun

“…In colposcopy-assisted diagnosis, the difference between the different lesion grades of colposcopic images is small, and the visual similarity is high. …”
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Modeling of Ultrasonic Flaw Detection Processes in the Task of Searching and Visualizing Internal Defects in Assemblies and Structures by B. V. Sobol, A. N. Soloviev, P. V. Vasiliev, A. A. Lyapin

“…The study uses the finite difference method in the time domain. It is applied to identify and visualize internal defects in materials using ultrasonic nondestructive testing and convolutional generative neural networks.Results. …”
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Probing Three-dimensional Magnetic Fields. IV. Synchrotron Polarization Derivative and Vision Transformer by Yue Hu, Alex Lazarian

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A Gesture Recognition Method Based on Deep Learning by DING Chi, LIN Jun, YOU Jun, YUAN Hao

“…In order to increase the accuracy and robustness of gesture recognition in video, and better utilize the advantages of different deep neural network architectures, it presented an approach to realize gesture recognition by combining multiple advanced convolutional neural network architectures. …”
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Research on Android malware detection method based on multimodal feature fusion by Ge Jike, He Mingkun, Chen Zuqin, Ling Jin, Zhang Yifan

“…Existing Android malware detection methods mainly use single-modal data to characterize program features, but fail to fully mine and fuse different feature information, resulting in unsatisfactory detection results. …”
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Visualization of internal defects using a deep generative neural network model and ultrasonic nondestructive testing by Р. V. Vasiliev, А. V. Senichev, I. Giorgio

“…The propagation of an ultrasonic wave is modeled by the finite difference method in the time domain. An ultrasonic signal received at the internal points of the control object is applied to the input of the convolutional neural network. …”
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Detecting Phishing URLs Based on a Deep Learning Approach to Prevent Cyber-Attacks by Qazi Emad ul Haq, Muhammad Hamza Faheem, Iftikhar Ahmad

“…Phishing is one of the most widely observed types of internet cyber-attack, through which hundreds of clients using different internet services are targeted every day through different replicated websites. …”
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CNN-based vane-type vortex generator modelling by Koldo Portal-Porras, Unai Fernandez-Gamiz, Ekaitz Zulueta, Roberto Garcia-Fernandez, Xabier Uralde-Guinea

“…In order to obtain data for training the network, 20 different CFD simulations were conducted, considering the same inflow conditions but different vane heights and angles of attack of the VGs. …”
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An automatic ICD coding method for clinical records based on deep neural network by Yichao DU, Tong XU, Jianhui MA, Enhong CHEN, Yi ZHENG, Tongzhu LIU, Guixian TONG

“…With the increase in the number of the international classification of diseases (ICD) codes,the difficulty and cost of manual coding based on clinical records have greatly increased,and automatic ICD coding technology has attracted widespread attention.A multi-scale residual graph convolution network automatic ICD coding technology was proposed.This technology uses a multi-scale residual network to capture text patterns of different lengths of clinical text and extracts the hierarchical relationship between labels based on the graph convolutional neural network to enhance the ability of automatic coding.The experimental results on the real medical data set MIMIC-III show that the P@k and Micro-F1 of this method are 72.2% and 53.9%,respectively,which significantly improves the prediction performance.…”
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Multimodal Chinese Sarcasm Detection Integrating Audio Attributes and Textual Features by Huixin Wu, Yang Zang, Limeng Zhao, Hongyang Zhou

“…To extract relevant features at different levels, we use a multi-scale convolutional architecture. …”
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Wavelet-CNN for temporal data: Enhancing long-term stock price prediction via multi-resolution wavelet decomposition and CNN-based feature extraction by Komei Hiruta, Junsuke Senoguchi

“…Specifically, we first acquire components with different temporal resolutions using wavelet transform, then convert the wavelet-transformed data into images, and finally perform CNN processing to automatically extract useful temporal features for prediction. …”
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From Pixels to Diagnosis: Implementing and Evaluating a CNN Model for Tomato Leaf Disease Detection by Zamir Osmenaj, Evgenia-Maria Tseliki, Sofia H. Kapellaki, George Tselikis, Nikolaos D. Tselikas

“…Our work involved the implementation of a custom convolutional neural network (CNN) trained on a diverse dataset of tomato leaf images. …”
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Potato Leaf Disease Detection Based on a Lightweight Deep Learning Model by Chao-Yun Chang, Chih-Chin Lai

“…In this paper, we present a novel approach that integrates a lightweight convolutional neural network architecture, RegNetY-400MF, with transfer learning techniques to accurately identify seven different types of potato leaf diseases. …”
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A Novel Multi-Task Learning-Based Approach to Multi-Energy System Load Forecasting by Zain Ahmed, Mohsin Jamil, Ashraf Ali Khan

“…Multi-Energy Systems (MES) allow optimal interactions between different energy sources. Accurate load forecasting for such intricate systems would greatly enhance the performance and economic incentive to employ them. …”
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Protection Algorithm Based on Two-Dimensional Spatial Current Trajectory Image and Deep Learning for Transmission Lines Connecting Photovoltaic Stations by Panrun Jin, Jianling Liao, Wenqin Song, Xushan Zhao, Yankui Zhang

“…In this algorithm, the PV side current and the system side current are, respectively, mapped to the two-dimensional space plane as X- and Y-axes to form the current trajectory image. Under different fault conditions, they have obvious differences. …”
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Multiscale deformed attention networks for white blood cell detection by Xin Zheng, Qiqi Xu, Shiyi Zheng, Luxian Zhao, Deyang Liu, Liangliang Zhang

“…Traditional WBC detection methods are labor-intensive and time-consuming. Convolutional Neural Networks (CNNs) are widely used for cell detection due to their strong feature extraction capability. …”
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