Integration of YOLOv8 Small and MobileNet V3 Large for Efficient Bird Detection and Classification on Mobile Devices by Axel Frederick Félix-Jiménez, Vania Stephany Sánchez-Lee, Héctor Alejandro Acuña-Cid, Isaul Ibarra-Belmonte, Efraín Arredondo-Morales, Eduardo Ahumada-Tello

“…Background: Bird species identification and classification are crucial for biodiversity research, conservation initiatives, and ecological monitoring. However, conventional identification techniques used by biologists are time-consuming and susceptible to human error. …”
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Neural Network-based CF4 and SF6/CF4 Detection in High Altitude and Extreme Cold Regions by Rukuo MA, Jie DONG, Yatian WANG, Guoxin YI, Xianghao DING, Le MA

“…To overcome this, an SF6 gas CF4 concentration detector utilizing pyroelectric detection technology was initially developed, capable of automatically switching among different ranges by selecting appropriate amplification resistances. …”
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SED-NET: Real-Time Suspicious Event Detection via Deep Learning-Based Di-Stream Neural Network by D. Siva Senthil, T. S. Sivarani

“…This research introduces a novel deep learning-based SED-NET model for detecting suspicious events in public places. Initially, input images are collected from two data for detecting Suspicious events. …”
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Suprasternal aortic arch echocardioscopy as a potential tool in detection and follow-up of mobile thrombi in patients with ischemic stroke by Inhar Esnaola Barriola, Elena Escriche Gorospe, Paula Miguel Navas, Elisa Martínez Campos, María Molina Goicoechea, Ferran Capell Pascual, Adrián Jiménez Delgado, Roberto Muñoz Arrondo

“…The aim of this study was to analyze the potential of echocardiographic examination through the suprasternal window in both the detection of embolic sources and the monitoring of the response to anticoagulant treatment in patients with mobile thrombi.MethodsThis case series study included ten consecutive patients with a mobile floating aortic arch thrombus associated with an atheromatous plaque, detected by focused echocardiography and confirmed by Computed Tomography Angiography (CTA). …”
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Accelerating Training of Convolutional Neural Networks With Hessian-Free Optimization for Detecting Alzheimer’s Disease in Brain MRI by Marios Pafitis, Maria Constantinou, Chris Christodoulou

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A hybrid learning approach for MRI-based detection of alzheimer’s disease stages using dual CNNs and ensemble classifier by Sepideh Zolfaghari, Atra Joudaki, Yashar Sarbaz

“…Computer-aided systems can help physicians in the early and accurate detection of AD, enabling timely intervention and effective management. …”
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Deep Electrical Resistivity Tomography for Detecting Gravitational Morpho-Structures in the Becca France Area (Aosta Valley, NW Italy) by Maria Gabriella Forno, Marco Gattiglio, Franco Gianotti, Cesare Comina, Andrea Vergnano, Stefano Dolce

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Early detection of myocarditis caused by immune checkpoint inhibitor therapy with nivolumab and ipilimumab for advanced recurrent renal cell carcinoma by Maki Todo, Yodo Gatate, Shintaro Nakano, Go Kaneko, Masayuki Hagiwara, Takayuki Takahashi, Yuta Umezawa, Genji Ueda, Shiho Ishikawa, Yoshinori Makino, Masafumi Oyama, Suguru Shirotake

“…Myocarditis due to this therapy was detected in 5 of the 86 patients (5.8%) assessed using the European Society of Cardiology 2022 guidelines. …”
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Smart Clothing and Medical Imaging Innovations for Real-Time Monitoring and Early Detection of Stroke: Bridging Technology and Patient Care by David Sipos, Kata Vészi, Bence Bogár, Dániel Pető, Gábor Füredi, József Betlehem, Attila András Pandur

“…These technologies support personalized care across the stroke continuum, from early risk detection and acute event monitoring to long-term recovery. …”
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The climate gluing protests: analyzing their development and framing in media since 1986 using sentiment analyses and frame detection models by Markus Hadler, Alexander Ertl, Beate Klösch, Markus Reiter-Haas, Elisabeth Lex

“…Using sentiment analysis and frame detection models, we analyze a corpus of all available English-language news articles in LexisNexis, with the first recorded instance of a gluing protest appearing in 1986. …”
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Multi-source data fusion-based knowledge transfer for unmanned aerial vehicle flight data anomaly detection and recovery by Lei Yang, Shaobo Li, Liya Yu, Caichao Zhu, Congbao Wang

“…Abstract Flight data anomaly detection (AD) is essential for unmanned aerial vehicle (UAV) health management. …”
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Evaluation of molecular mouse sepsis panel: new portable and rapid tests for microorganism detection in suspected blood stream infection by Claudia Colosimo, Claudia Colosimo, Maria Sofia Montanari, Maria Sofia Montanari, Anna Marzucco, Anna Marzucco, Giulia Gatti, Giulia Gatti, Lucrezia Puccini, Laura Grumiro, Laura Grumiro, Laura Dionisi, Laura Dionisi, Martina Brandolini, Martina Brandolini, Ludovica Ingletto, Ludovica Ingletto, Massimiliano Guerra, Giorgio Dirani, Silvia Zannoli, Alessandra Scagliarini, Alessandra Mistral De Pascali, Alessandra Mistral De Pascali, Vittorio Sambri, Vittorio Sambri, Monica Cricca, Monica Cricca

“…This study aims to evaluate the performance of MM cartridges in detecting Gram-positive bacteria and Gram-negative bacteria, as well as their associated resistance genes, using clinical leftover positive BCs and contrived samples for low-prevalence targets. …”
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Automatic Fracture Detection Convolutional Neural Network with Multiple Attention Blocks Using Multi-Region X-Ray Data by Rashadul Islam Sumon, Mejbah Ahammad, Md Ariful Islam Mozumder, Md Hasibuzzaman, Salam Akter, Hee-Cheol Kim, Mohammad Hassan Ali Al-Onaizan, Mohammed Saleh Ali Muthanna, Dina S. M. Hassan

“…Accurate detection of fractures in X-ray images is important to initiate appropriate medical treatment in time—in this study, an advanced combined attention CNN model with multiple attention mechanisms was developed to improve fracture detection by deeply representing features. …”
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RETRACTED: An Infrared Small Target Detection Method Based on a Weighted Human Visual Comparison Mechanism for Safety Monitoring by Yuanyuan Chen, Huiqian Wang, Yu Pang, Jinhui Han, En Mou, Enling Cao

“…Infrared small target detection is a crucial technology in both military and civilian applications, including surveillance, security, defense, and combat. …”
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Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images by Chi-en Amy Tai, Elizabeth Janes, Chris Czarnecki, Alexander Wong

“…This paper explores leveraging an efficient self-attention structure to detect skin cancer in skin lesion images and introduces a deep neural network design with DC-AC customized for skin cancer detection from skin lesion images. …”
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Economic evaluations of screening strategies for the early detection of colorectal cancer in the average-risk population: A systematic literature review. by Joan Mendivil, Marilena Appierto, Susana Aceituno, Mercè Comas, Montserrat Rué

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Empowering Kelon (Oncology Class) in Screening and Early Detection of Breast Cancer in The South Pekalongan Health Centre Working Area by Isrofah Isrofah, Dani Prastiwi, Rr. Vita Nurlatif, Irene Dwitasari Wulandari

“…Early screening measures need to be done to detect abnormal cells before they develop into deadly cancer. …”
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Artificial intelligence with feature fusion empowered enhanced brain stroke detection and classification for disabled persons using biomedical images by Mohammed Alsieni, Khaled H. Alyoubi

“…Artificial intelligence technologies, primarily deep learning (DL), have been widely employed in medical imaging, utilizing automated detection methods. This paper presents an Enhanced Brain Stroke Detection and Classification using Artificial Intelligence with Feature Fusion Technologies (EBSDC-AIFFT) model. …”
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Advanced object detection for smart accessibility: a Yolov10 with marine predator algorithm to aid visually challenged people by Mahir Mohammed Sharif Adam, Hussah Nasser AlEisa, Samah Al Zanin, Radwa Marzouk

“…They face problems with such actions and object detection should be an essential feature they can rely on a regular basis. …”
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Integration of metaheuristic based feature selection with ensemble representation learning models for privacy aware cyberattack detection in IoT environments by M. Karthikeyan, R. Brindha, Maria Manuel Vianny, V. Vaitheeshwaran, Mrinal Bachute, Sanket Mishra, Bibhuti Bhusan Dash

“…This manuscript proposes an Adaptive Metaheuristic-Based Feature Selection with Ensemble Learning Model for Privacy-Preserving Cyberattack Detection (AMFS-ELPPCD) technique. The data normalization stage initially applies Z-score normalization to convert input data into a beneficial format. …”
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