Aircraft Pilot Assistance System: Detection of Other Aircraft Using Artificial Neural Networks by Tomiło Paweł

“…In the development process, different types of solutions as well as sizes of detection models were tested. …”
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Deep learning for rice leaf disease detection: A systematic literature review on emerging trends, methodologies and techniques by Chinna Gopi Simhadri, Hari Kishan Kondaveeti, Valli Kumari Vatsavayi, Alakananda Mitra, Preethi Ananthachari

“…Most of the earlier studies on rice leaf disease detection depended on image processing and machine learning techniques. …”
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Integration of Arc and Microstructural Analysis for Anomaly Detection in Walls Manufactured by GMA-Based WAAM by Lucas J. E. B. Santos, Joyce I. V. Souto, Igo J. S. Azevedo, Walman B. Castro, Jefferson S. Lima, João M. P. Q. Delgado, Renato A. C. Santana, Ricardo S. Gomez, André L. D. Bezerra, Antonio G. B. Lima

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Multi-Level Graph Attention Network-Based Anomaly Detection in Industrial Control System by Longxin Lin, Anyang Gu, Feiyan Min, Shan Zhou

“…Experiments on two real-world ICS datasets demonstrate that PCGAT achieves superior performance and enables the localization of anomalies within specific physical processes. Moreover, by leveraging graph attention networks (GATs), PCGAT enhances interpretability in anomaly detection.…”
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Deep learning-based detection of indicator species for monitoring biodiversity in semi-natural grasslands by Deepak H. Basavegowda, Inga Schleip, Paul Mosebach, Cornelia Weltzien

“…Here, we developed a DL-based object-detection model to identify indicator species, a group of vascular plant species that serve as surrogates for biodiversity assessment in high nature value (HNV) grasslands. …”
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Monitoring the long-term molecular epidemiology of the pneumococcus and detection of potential 'vaccine escape' strains. by Gagan A Pandya, M Catherine McEllistrem, Pratap Venepally, Michael H Holmes, Behnam Jarrahi, Ravi Sanka, Jia Liu, Svetlana A Karamycheva, Yun Bai, Robert D Fleischmann, Scott N Peterson

“…The phylogenetic analysis of the 11 concatenated genes was performed with the MrBayes program, the single nucleotide polymorphism (SNP) analysis with the DNA Sequence Polymorphism program (DnaSP), and the recombination event analysis with the recombination detection package (RDP).…”
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Molecular detection and characterization of spotted fever group Rickettsia and Anaplasma in ticks from Pakistan by Khan Sadia Salim, Ahmed Haroon, Benedict S. Khoo, Evan J. Kipp, Abid Ali, Davide Sassera, Muhammad Umair Aziz, Jonathan D. Oliver

“…PCR amplification of the ompA gene was used for detection of Rickettsia and portions of the 16S rDNA gene for detection of Anaplasma. …”
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Application of semi-supervised object detection technology incorporating attention mechanism in rail transit by WANG Junyu, CHEN Zhe, SUN Junyong

“…This paper proposes a semi-supervised object detection strategy that incorporates an attention mechanism, to reduce the cost of data processing and improve the robustness of the models. …”
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Detection of Masses in Mammogram Images Based on the Enhanced RetinaNet Network With INbreast Dataset by Wang M, Liu R, Luttrell IV J, Zhang C, Xie J

“…Until now, analyzing mammogram images is still the main method used by doctors to diagnose and detect breast cancers. However, this process usually depends on the experience of radiologists and is always very time consuming.Patients and Methods: We propose to introduce deep learning technology into the process for the facilitation of computer-aided diagnosis (CAD), and address the challenges of class imbalance, enhance the detection of small masses and multiple targets, and reduce false positives and negatives in mammogram analysis. …”
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SurfaceVision: An Automated Module for Surface Fault Detection in 3D Printed Products by Laukesh Kumar, Manoj Kumar Satyarthi

“…Machine learning techniques being used for automatic detection of the faults suffer in real time conditions with inefficient fault detection due to the inability of adaptation to real time changes in the printing process. …”
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Causal analysis and impact of a systematic error detected about consumption associated with trastuzumab by Nuria Bujaldón Querejeta, Dolores Camacho Romera, José Antonio Pomares Pastor, María Sánchez Garnes, Mauricio Martínez Ramírez, Mercedes González Delgado

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Development of YOLO-Based Mobile Application for Detection of Defect Types in Robusta Coffee Beans by Eko Dwi Nugroho, Miranti Verdiana, Muhammad Habib Algifari, Aidil Afriansyah, Hafiz Budi Firmansyah, Alya Khairunnisa Rizkita, Richard Arya Winarta, David Gunawan

“…However, the identification of defects in coffee beans is still largely performed manually, making the process error-prone and time-consuming. This study aims to develop a YOLO-based mobile application to detect defects in Robusta coffee beans quickly and accurately. …”
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Fine-Tuned Visual Transformer Masked Autoencoder Applied for Anomaly Detection in Satellite Images by Jakub Gajda, Joanna Kwiecień

“…Anomaly detection is a process in which outlier samples can be detected in a given dataset. …”
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iOLE—Human-Centered Software Design for Leakage Detection in Water Distribution Networks by Ivo Daniel, David Steffelbauer, Ella Steins, Jonas Schorr, Sophie Persigehl, Enrique Campbell, Johannes Koslowski, Jens Kley-Holsteg, Bernd Lindemann, Andrea Cominola

“…Despite numerous technological advances, the adoption of digital leakage detection technology remains a slow process. Here, we present the project iOLE—intelligent Online LEakage detection, where we aim to increase the applicability of automated leak detection in practice through enhanced user experience and detection robustness. iOLE employs a human-centered design approach that involves the feedback of potential users during its development process to maximize subsequent user acceptance. …”
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Combination of Individual Tests to Improve Diagnostic Accuracy in <i>Chlamydia trachomatis</i> Detection by Jelena Tošić-Pajić, Predrag Sazdanović, Aleksandar Nikolov, Dragan R. Milovanović, Violeta Ninković, Jelena Čukić, Slobodan Subotić, Marija Šorak, Dejan Baskić

“…Despite all national programs, strategies and guidelines, chlamydial infection is still the leading infection worldwide, especially in young populations. …”
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Environmental DNA Methods for Detection of Varroa destructor in Honey Bee (Apis mellifera) Hives by John M. K. Roberts, Richard J. Hall, Foyez Shams, Francisco Encinas‐Viso, Florence Bravo, Jenn Soroka, Liz Milla, Natale Snape, Francesco Martoni, Antonette Walford, Dianne Gleeson, Alejandro Trujillo‐González

“…Using varroa‐free hives introduced from the Chatham Islands to Wellington, New Zealand, we were also able to show that V. destructor eDNA was detectable during the initial invasion of hives. Our data highlight the potential for incorporating eDNA methods into Australia's biosecurity surveillance programs to help limit the spread of varroa mites to new areas and detect future incursions.…”
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Carbon dot-assisted synthesis of gold nanoparticles for the development of a detection platform for trichlorfon by Pramila Murugesan, J.A. Moses

“…Owing to their unique physicochemical features, gold nanoparticles (AuNPs) stand out as an excellent platform for analyte detection with appreciable accuracy. In this study, a low-cost precursor material was used to synthesize hydrophilic functional groups containing carbon dots (CD) and then used as a stabilizing and reducing agent for synthesizing AuNPs via a one-step process. …”
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Towards the development of an algorithm for automatic analysis and detection of shock waves in the schlieren visualization technique by George Ionut VRABIE, Andrei V. COJOCEA, Mihnea GALL, Constantin ANTON, Daniel C. ASOLTANEI, Ionut PORUMBEL

“…This paper presents the development of an algorithm for identifying shock waves formed during the supersonic combustion process, detonation, in a pulsed detonation chamber. …”
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Explainable one-class feature extraction by adaptive resonance for anomaly detection in quality assurance. by Hootan Kamran, Dionne Aleman, Chris McIntosh, Tom Purdie

“…By offering clear insights into decision-making processes, our method allows healthcare professionals to quickly identify and address specific deficiencies in RT plans deemed unacceptable, thereby streamlining the QA process and enhancing patient care efficiency and safety.…”
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Interpretable adaptive fault detection method for smart grid based on belief rule base by Yingmei Li, Yaopu Bai, Ruohan Yang, Zhichao Feng, Wei He

“…This method considers the adaptive updating of the search domain of the model accuracy to achieve the balance and optimization between the two conflicting objectives of the model interpretability and the detection accuracy. The fault detection model based on AI-BRB considers the interpretability of modeling, inference and optimization processes. …”
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