Topic Words-Based Multilingual Hateful Linguistic Resources Construction for Developing Multilingual Hateful Content Detection Model Using Deep Learning Technique by Naol Bakala Defersha, Kula Kekeba Tune, Solomon Teferra Abate

“…Finally, their performance was compared by integrating them into deep learning-based low-resource Ethiopian languages’ hateful content detection framework. …”
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Comparison of Directional and Diffused Lighting for Pixel-Level Segmentation of Concrete Cracks by Hamish Dow, Marcus Perry, Jack McAlorum, Sanjeetha Pennada

“…Visual inspections of concrete infrastructure in low-light environments require external lighting to ensure adequate visibility. …”
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Diagnostics and Prognostics of Boilers in Power Plant Based on Data-Driven and Machine Learning by Achmad Widodo, Toni Prahasto, Mochamad Soleh, Herry Nugraha

“…The results show that some anomalies are successfully detected by prediction model even though there are anomalies that give low accuracies in predictions. …”
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Artificial Intelligence-Assisted Segmentation of a Falx Cerebri Calcification on Cone-Beam Computed Tomography: A Case Report by Julien Issa, Alexandre Chidiac, Paul Mozdziak, Bartosz Kempisty, Barbara Dorocka-Bobkowska, Katarzyna Mehr, Marta Dyszkiewicz-Konwińska

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Optimizing an image analysis protocol for ocean particles in focused shadowgraph imaging systems by Huanqing Huang, Alexander B. Bochdansky

“…To improve reconstruction of particles captured by Focused Shadowgraph Imaging (FoSI)—a system that excels at visualizing low-optical-density objects, we developed a novel object detection algorithm to process images with a resolution of ~ 12 μm per pixel. …”
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AISLEX: Approximate individual sample learning entropy with JAX by Ondrej Budik, Milan Novak, Florian Sobieczky, Ivo Bukovsky

“…We present AISLEX, an online anomaly detection module based on the Learning Entropy algorithm, a novel machine learning-based information measure that quantifies the learning effort of neural networks. …”
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Gaze cluster analysis reveals heterogeneity in attention allocation and predicts learning outcomes by Nathalie John, Sebastian P. Korinth, Mareike Kunter, Franziska Baier-Mosch

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A Pervasive Respiratory Monitoring Sensor for COVID-19 Pandemic by Xiaoshuai Chen, Shuo Jiang, Zeyu Li, Benny Lo

“…Thus, a low-cost pervasive ambient sensor is proposed. <italic>Methods:</italic> We will posit a barometer on the working desk and develop a novel signal processing algorithm with a sparsity-based filter to remove the similar-frequency noise. …”
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Third Ventricle Width Measurements Based on YOLO and Localized Intensity Features by Xiao Zhou, Ao Wan, Xingang Mou, Hongling Gao, Zheng Xue

“…Firstly, to solve the problem of third ventricle detection in the complex background of TCS images, the YOLO-TV improvement model is proposed to improve the detection accuracy. …”
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EPCNet: Implementing an ‘Artificial Fovea’ for More Efficient Monitoring Using the Sensor Fusion of an Event-Based and a Frame-Based Camera by Orla Sealy Phelan, Dara Molloy, Roshan George, Edward Jones, Martin Glavin, Brian Deegan

“…To reduce system latency, a novel object detection approach is proposed where the event camera acts as a region proposal network, and a classification algorithm is run on the proposed regions. …”
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LUNGINFORMER: A Multiclass of lung pneumonia diseases detection based on chest X-ray image using contrast enhancement and hybridization inceptionresnet and transformer by Hanafi Hanafi

“…To address the problem, many researchers have employed deep learning algorithms to develop an automated detection system for pneumonia. …”
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LR-FHSS Transceiver for Direct-to-Satellite IoT Communications: Design, Implementation, and Verification by Sooyeob Jung, Seongah Jeong, Jinkyu Kang, Gyeongrae Im, Sangjae Lee, Mi-Kyung Oh, Joon Gyu Ryu, Joonhyuk Kang

“…Moreover, we apply a robust synchronization scheme against the Doppler effect and co-channel interference (CCI) caused by LEO satellite channel environments, including signal detection for the simultaneous reception of numerous frequency hopping signals and an enhanced soft-output-Viterbi-algorithm (SOVA) for the header and payload receptions. …”
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MFFCI&#x2013;YOLOv8: A Lightweight Remote Sensing Object Detection Network Based on Multiscale Features Fusion and Context Information by Sheng Xu, Lin Song, Junru Yin, Qiqiang Chen, Tianming Zhan, Wei Huang

“…There is a growing need for lightweight algorithms in certain remote sensing devices. Moreover, remote sensing images (RSIs) often contain numerous small, densely distributed targets, which pose significant detection challenges. …”
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Machine Learning Aided Resilient Spectrum Surveillance for Cognitive Tactical Wireless Networks: Design and Proof-of-Concept by Eli Garlick, Nourhan Hesham, MD. Zoheb Hassan, Imtiaz Ahmed, Anas Chaaban, MD. Jahangir Hossain

“…Conventional supervised machine learning (ML) algorithm&#x2019;s capability to provide spectrum awareness is confronted by the requirement of labeled interference signals. …”
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Text-Guided Synthesis in Medical Multimedia Retrieval: A Framework for Enhanced Colonoscopy Image Classification and Segmentation by Ojonugwa Oluwafemi Ejiga Peter, Opeyemi Taiwo Adeniran, Adetokunbo MacGregor John-Otumu, Fahmi Khalifa, Md Mahmudur Rahman

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Subsurface cavity detection in a karst environment using electrical resistivity (er): a case study from yongweol-ri, South Korea by Farooq Muhammad, et al

“…The resistivity data was inverted using 2D and 3D algorithms based on the least squares smoothness constraint technique. …”
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Cervical cancer demystified: exploring epidemiology, risk factors, screening, treatment modalities, preventive measures, and the role of artificial intelligence by N. Mohammad, M. Khan, M. Maqsood, A. H. K. Naseeb

“…Cervical cancer remains a significant global health challenge, particularly in low- and middle-income countries where access to preventive measures and early detection is limited. …”
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A Machine-Learning-Based Analysis of Resting State Electroencephalogram Signals to Identify Latent Schizotypal and Bipolar Development in Healthy University Students by Flórián Gubics, Ádám Nagy, József Dombi, Antónia Pálfi, Zoltán Szabó, Zsolt János Viharos, Anh Tuan Hoang, Vilmos Bilicki, István Szendi

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Anomaly classification in IIoT edge devices by Danny Alexandro Múnera-Ramírez, Diana Patricia Tobón-Vallejo, Martha Lucía Rodríguez-López

“…A k-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), and Multilayer Perceptron (MLP) algorithms were trained. Considering metrics such as false positive rate, false negative rate, accuracy, F1-score, and execution time, we concluded that SVM and MLP were the best methods for the case study because of their accuracy (78.6 and 76.1, respectively) and low execution time (17.3ms and 0.35ms). …”
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A Monocular Vision-Based Safety Monitoring Framework for Offshore Infrastructures Utilizing Grounded SAM by Sijie Xia, Rufu Qin, Yang Lu, Lianjiang Ma, Zhenghu Liu

“…The experimental results and case study suggest that the framework has notable advantages, including low cost, convenient deployment with minimal maintenance, high detection accuracy, and strong adaptability to diverse application conditions, which brings a supplemental solution to research on offshore infrastructure safety.…”
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