Transfer learning from inorganic materials to ivory detection by Agil Aghasanli, Plamen Angelov, Dmitry Kangin, Jemma Kerns, Rebecca Shepherd

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Single-event upset simulation and detection in configuration memory by Hezekiah Austin, Chris Major, Chris Major, Colter Barney, Justin Williams, Zachary Becker, Mackenzie Smith, Brock LaMeres, Brock LaMeres

“…Injection throughout the configuration memory was used to create a map of particularly vulnerable locations in configuration memory and the implemented logic design. …”
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Detection of Defects on Metal Surfaces Based on Deep Learning by Onur Cem Han, Uğurhan Kutbay

“…Image preprocessing techniques such as morphological operations, Gaussian noise addition, Principal Component Analysis, and image thresholding with Otsu thresholding were used for defect detection. The model was trained using the newly created database, achieving a successful result with an average accuracy rate of 87% using the proposed algorithm.…”
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Henri La Barthe, l’inventeur de Détective by Dominique Kalifa

“…The famous magazine Detective founded by Gallimard and the brothers Kessel was first a professional gazette created in 1925 by the private detective Henri La Barthe, who sold it to Gaston Gallimard three years later. …”
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Detection of Apple Trees in Orchard Using Monocular Camera by Stephanie Nix, Airi Sato, Hirokazu Madokoro, Satoshi Yamamoto, Yo Nishimura, Kazuhito Sato

“…An original dataset of orchard images was created and used to train Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO) models. …”
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Detection of Face Direction by Implementing Face Edge Patterns by Jarjees Khidir

“…In this paper, a method for detecting the direction of a human face is developed; regardless of its age or sex.  …”
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Large Language Models for Detecting Bias in Job Descriptions by Tristan Everitt, Paul Ryan, Brian Davis, Kolawole J. Adebayo

“…This study explores the application of large language (LLM) models for detecting implicit bias in job descriptions, an important concern in human resources that shapes applicant pools and influences employer perception. …”
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Detection of Frauds in Deep Fake Using Deep Learning by Osipilli Aparna, Pakanati Rani, Tulluri Ramya, Tanneru Priyanka, Neela Sundari, P. G. K. Sirisha, Repudi Ramesh, Dama Anand

“…We will also examine the problems in building a generalized DeepFake detection model. Lastly, the difficulties in creating and identifying DeepFakes will be covered.…”
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E-Exam Cheating Detection System for Moodle LMS by Ahmed S. Shatnawi, Fahed Awad, Dheya Mustafa, Abdel-Wahab Al-Falaky, Mohammed Shatarah, Mustafa Mohaidat

“…Although existing solutions aim to prevent and detect such misconduct, they often face limitations that make them impractical for many educational institutions. …”
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Detecting anomalous SRF cavity behavior with unsupervised learning by Hal Ferguson, Jiang Li, Adam Carpenter, Chris Tennant, Dillon Thomas, Dennis Turner

“…Key to the system’s success was the development of data acquisition systems (DAQs) that capture fast-sampled, information-rich signals, essential for detecting transient effects. The approach involves creating daily cavity-specific models using principal component analysis to handle variations in rf signal behavior and mitigate performance degradation from data drift. …”
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Perspectives on the Application of Biosensors for the Early Detection of Oral Cancer by Sanket Naresh Nagdeve, Baviththira Suganthan, Ramaraja P. Ramasamy

“…The paper provides an epidemiological and etiological overview, outlining its clinical importance and reviewing the current state of the art in detection methods. Despite considerable progress, conventional methods exhibit limitations such as invasiveness, long wait times, and a lack of accuracy, creating a critical need for more robust technologies. …”
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Xanthogranulomatous Pyelonephritis Incidentally Detected in a Young Infant by Jeena Annie Philip, R. Veena, Christy Cathreen Thomas, Radhika C. Radhakrishnan, Ashok Kumar, Susan Uthup

“…Examination showed tachypnea, normal pulses, improper weight gain since birth, hypertension and was incidentally detected to have palpable right kidney, without any abnormality in urinary stream. …”
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Anomaly detection in medical via multimodal foundation models by Zhenyou Tang, Zhong Tang, Jing Wu

“…IntroductionRecent advances in artificial intelligence have created opportunities for medical anomaly detection through multimodal learning frameworks. …”
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Marble Surface Anomaly Detection Using Autoencoder Architecture by Yahya Abdullah, Cemil Öz

“…Due to the many uses of marble in various aspects, marble surface detection is important for this industry to improve quality and avoid financial problems that may occur. …”
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An Ensemble Learning Approach for Glaucoma Detection in Retinal Images by Marwah M. Mahdi, Mohammed Abdulkreem Mohammed, Haider Al-Chalibi, Bashar S. Bashar, Hayder Adnan Sadeq, Talib Mohammed Jawad Abbas

“…In this study, a CNN-based deep learning architecture is created for the categorization of normal and glaucomatous fundus pictures. …”
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An ensemble of modern computer vision models for deepfake detection by Aleksandr S. Pikul

“…The dataset for the experiment was created from video frames containing deepfakes, and these frames were subjected to various augmentations. …”
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Detection of Montage in Lossy Compressed Digital Audio Recordings by Rafał KORYCKI

“…This paper addresses the problem of tampering detection and discusses methods used for authenticity analysis of digital audio recordings. …”
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A survey of 3D object detection algorithms by Zhe HUANG, Yongcai WANG, Deying LI

“…3D object detection is a fundamental problem in autonomous driving，virtual reality，robotics，and other applications.Its goal is to extract the most accurate 3D box characterizing interested targets from the disordered point clouds，such as the closest 3D box surrounding the pedestrians or vehicles.The target 3D box's location，size，and orientation are also output.Currently，there are two primary approaches for 3D object detection: (1) pure point cloud based 3D object detection，in which the point clouds are created by binocular vision，RGB-D camera，and lidar; (2) fusion-based 3D object detection based on the fusion of image and point cloud.The various representations of 3D point clouds were introduced.Then representative methods were introduced from three aspects: traditional machine learning techniques; non-fusion deep learning based algorithms; and multimodal fusion-based deep learning algorithms in progressive relation.The algorithms within and across each category were examined and compared，and the differences and connections between the various methods were analyzed thoroughly.Finally，remaining challenges of 3D object detection were discussed and explored.And the primary datasets and metrics used in 3D object detection studies were summarized.…”
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Detection of polysaccharides from local algae in fresh water by Nawras Al-Rikabi, Roa'a Jaafar Khairallah

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A Novel Method for Community Detection in Bipartite Networks by Ali Khosrozadeh, Ali Movaghar, Mohammad Mehdi Gilanian Sadeghi, Hamidreza Mahyar

“…Typically, in bipartite networks, a unipartite projection of one part of the network is created, and then communities are detected inside that projection using methods for unipartite networks. …”
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