Neurocysticercosis by Osvaldo M. Takayanagui

“…Cysticercosis is one of the most common parasitic diseases of the nervous system in humans, and constitutes a major public health problem for most of the developing world. The clinical manifestations of neurocysticercosis (NCC) largely depend on the the host immune response against the parasite. …”
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A swin transformer and CNN fusion framework for accurate Parkinson disease classification in MRI by Sayyed Shahid Hussain, Pir Masoom Shah, Hussain Dawood, Xu Degang, Ahmad Alshamayleh, Muhammad Adnan Khan, Taher M. Ghazal

“…Convolutional neural networks (CNNs) have been extensively employed in Parkinson’s disease (PD) detection using MR images. However, CNN models generally focus on local features while prone to capture global representations. …”
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Attention-CARU With Texture-Temporal Network for Video Depth Estimation by Sio-Kei Im, Ka-Hou Chan

“…RNN-based encoder-decoder architectures are the most commonly used methods for depth feature prediction, but recurrent operators have limitations of large-scale perspective from global information and also face the long-term dependency problem, which often leads to inaccurate prediction of object depth in complex scenes. …”
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Deghosting method for cross localization in distributed high frequency surface wave radar by Na Cui, Xuekun Chen, Changjun Yu

“…Abstract In this article, the challenging problem of multi‐target cross localization within a novel distributed high‐frequency surface wave radar (HFSWR) is tackled. …”
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Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings by David Verstraete, Andrés Ferrada, Enrique López Droguett, Viviana Meruane, Mohammad Modarres

“…This knowledge is sometimes a luxury and could introduce added uncertainty and bias to the results. To address this problem a deep learning enabled featureless methodology is proposed to automatically learn the features of the data. …”
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Surface Eddy Current Probes: Excitation Systems of the Optimal Electromagnetic Field (Review) by V. Ya. Halchenko, R. V. Trembovetskaya, V. V. Tychkov

“…Development of technical tools with improved metrological and operational characteristics is the actual problem of the eddy current testing. Ensuring the optimal distribution of the electromagnetic excitation field in the testing zone carries out confident detection of the defects and determination of their geometrical parameters by means of eddy current testing. …”
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Digits Recognition for Arabic Handwritten through Convolutional Neural Networks, Local Binary Patterns, and Histogram of Oriented Gradients by Bushra Mahdi Hasan, Zahraa Jasim Jaber, Ahmad Adel Habeeb

“…In addition, a Histogram of Oriented Gradients (HOG) is a feature extraction technique that is used in computer vision and image processing for the purpose of object detection. …”
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Screening for depression at the primary care level: Evidence for policy decision-making from a facility in Pretoria, South Africa by Bahupileng L. Mashaba, Saiendhra V. Moodley, Neo R.T. Ledibane

“…Conclusion: Depression appears to be a significant problem in PHC settings in South Africa. Screening for depressive features at primary level, targeting those with chronic medical conditions, history of recent stressful life events and other known risk factors may improve detection rates, lead to earlier diagnosis and improved health outcomes.…”
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MEDULLARY CARCINOMA OF THE BREAST: ROENTGENOLOGIC AND ULTRASOUND SEMIOTICS by A. B. Abduraimov, K. A. Lesko, V. Yu. Pletneva, I. A. Blokhin

“…This problem leads to necessity find reliable distinguishing features in mammograpic and ultrasound semiotics. …”
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A Holistic Strategy of Modified Superpixel Segmentation and Randomized Adam Hyperparameter Tuning with Deep Learning Approaches for the Classification of Breast Cancer from BreakHi... by Gowri Shankar Manivannan, Karthikeyan Shanmugam, Harikumar Rajaguru, Satish V. Talawar, Rajanna Siddaiah

“…In this study, an integrated breast cancer detection approach using BreakHis images is proposed focusing on balanced accuracy rate analysis to solve imbalanced datasets problem. …”
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A Weighted-Transfer Domain-Adaptation Network Applied to Unmanned Aerial Vehicle Fault Diagnosis by Jian Yang, Hairong Chu, Lihong Guo, Xinhong Ge

“…The method is based on unsupervised transfer learning, which can transfer the knowledge learnt from existing datasets to solve problems in the target domain. The method contains three novel multiscale modules: a feature extractor, used to extract multidimensional features from the input; a domain discriminator, used to improve the imbalance of the data distribution between the source domain and the target domain; and a label classifier, used to classify data categories for the target domain. …”
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RECOGNITION OF PROPELLER-DRIVEN AIRCRAFT IN A PASSIVE BISTATIC RADAR by E. N. Vorobev, V. I. Veremyev, D. V. Kholodnyak

“…Nowadays passive bistatic radars (PBR) allow for detection, determination of coordinates and tracking of moving objects. …”
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Monitoring the reliability of integrated circuits protection against Trojans: encoding and decoding of combinational structures by L. A. Zolotorevich, V. A. Ilyinkov

“…The emergence of counterfeit integrated circuits, problems of piracy, overproduction, unauthorized interference in the design of microcircuit, hardware Trojans require the development of methods and means of their timely detection. …”
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Collaborative Big Data Management and Analytics in Complex Systems with Edge 2021 eaCamera: A Case Study on AI-Based Complex Attention Analysis with Edge System by Chaopeng Guo, Peimeng Zhu, Feng Li, Jie Song

“…In this paper, we study the problem of attention detection. Attentional concentration during some specific tasks plays a vital role, which indicates the effectiveness and performance of human beings. …”
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EDPNet: A Transmission Line Ice-Thickness Recognition End-Side Network Based on Efficient Dynamic Perception by Yangyang Jiao, Yu Zhang, Yinke Dou, Liangliang Zhao, Qiang Liu

“…Compared with the baseline model, the maximum ice-thickness detection error is 4.2%, the model parameters are reduced by 86.1%, and the detection speed is increased by 74.6%. …”
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Toward Inclusive Smart Cities: Sound-Based Vehicle Diagnostics, Emergency Signal Recognition, and Beyond by Amr Rashed, Yousry Abdulazeem, Tamer Ahmed Farrag, Amna Bamaqa, Malik Almaliki, Mahmoud Badawy, Mostafa A. Elhosseini

“…Evaluations using both compact (52 features) and expanded (126 features) representations show that several classes (e.g., Engine Misfire, Fuel Pump Cartridge Fault, Radiator Fan Failure) achieve near-perfect accuracy, though acoustically similar classes like Universal Joint Failure, Knocking, and Pre-ignition Problem remain challenging. …”
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Behavior Analysis of Students in Preschool Mathematics Teaching Based on Deep Learning by Guangning Qin

“…Through convolution and self-attention mechanism, multi-scale feature fusion is enhanced. Adding a small target detection layer and extracting local features from larger-sized feature maps significantly improves the ability to recognize the behaviors of students in the back row. …”
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Learning Condition-Invariant Scene Representations for Place Recognition across the Seasons Using Auto-Encoder and ICA by Tariqul Islam, Sheikh Rabiul Islam, Mahbubur Rahman

“…However, the map becomes inconsistent when the robot moves in the environment and detects errors with emotional accuracy. The loop-closure detection is the process through which a robot can acknowledge the location visited previously, which can identify the ultimate solution to the previous problem. …”
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Knowledge Graph Representation Fusion Framework for Fine-Grained Object Recognition in Smart Cities by Yang He, Ling Tian, Lizong Zhang, Xi Zeng

“…Autonomous object detection powered by cutting-edge artificial intelligent techniques has been an essential component for sustaining complex smart city systems. …”
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Emotion classification with multi‐modal physiological signals using multi‐attention‐based neural network by Chengsheng Zou, Zhen Deng, Bingwei He, Maosong Yan, Jie Wu, Zhaoju Zhu

“…However, emotion classification with physiological signals is still a challenging problem due to the diversity of emotion expression and the characteristic differences in different modal signals. …”
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