A Fault Detection Framework for Rotating Machinery with a Spectrogram and Convolutional Autoencoder by Hoyeon Lee, Jaehong Yu

“…Finally, we construct the fault detection model by applying the one-class classification algorithm to the latent feature vectors of training signals. …”
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Autonomous Streaming Space Objects Detection Based on a Remote Optical System by V. S. Baranova, V. A. Saetchnikov, A. A. Spiridonov

“…Under laboratory conditions, the satellite trajectory had simulated for an initial assessment of the compiled algorithmic modules of the computer vision library OpenCV.Based on the simulation results, dynamic detection of the International Space Station in real-time from the observation site with coordinates longitude 25o41′49″ East, latitude 53o52′36″ North in the interval 00:54:00–00:54:30 17.07.2021 (UTC + 03:00) had performed. …”
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Pear Fruit Detection Model in Natural Environment Based on Lightweight Transformer Architecture by Zheng Huang, Xiuhua Zhang, Hongsen Wang, Huajie Wei, Yi Zhang, Guihong Zhou

“…Aiming at the problems of low precision, slow speed and difficult detection of small target pear fruit in a real environment, this paper designs a pear fruit detection model in a natural environment based on a lightweight Transformer architecture based on the RT-DETR model. …”
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UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions by Charles Buchanan, Gogulan Karunanithy, Olga Tkachenko, Michael Barber, Michael T. Marty, Timothy J. Nott, Christina Redfield, Andrew J. Baldwin

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Explainable few-shot learning workflow for detecting invasive and exotic tree species by Caroline M. Gevaert, Alexandra Aguiar Pedro, Ou Ku, Hao Cheng, Pranav Chandramouli, Farzaneh Dadrass Javan, Francesco Nattino, Sonja Georgievska

“…While few-shot learning algorithms can address the first problem, they still lack sufficient explanations for the results. …”
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Leveraging advanced technologies for early detection and diagnosis of oral cancer: Warning alarm by Saantosh Saravanan, N. Aravindha Babu, Lakshmi T, Mukesh Kumar Dharmalingam Jothinathan

“…The medical technology, particularly in the areas of deep learning, optimization algorithms, and imaging techniques, has begun a new paradigm in oral cancer diagnosing and detecting methodologies. …”
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Federated knowledge distillation for enhanced insulator defect detection in resource‐constrained environments by Xiaohu Huang, Minghui Jia, Xianghua Tai, Wei Wang, Qi Hu, Dongping Liu, Peiheng Guo, Shengxiang Tian, Dequan Yan, Haishan Han

“…However, the existing high‐quality insulator defect detection models still face problems such as relying on massive‐labelled data and huge model parameters. …”
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Single-Frame Infrared Target Detection Based on Fast Content-Related Modeling by Zipeng Zhang, Xidong Zhao, Wenzheng Wang, Yuqi Han, Chenwei Deng, Zhuokai Li, Linbo Tang

“…Most of methods mainly concentrate on modeling global features, overlooking the variations in local features due to complex scenes. To solve these problems, a single-frame infrared target detection method based on fast content-related modeling is proposed to combine global and local features of infrared images, describing the common features of varying scenes robustly and enhancing the distinction between targets and backgrounds. …”
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Using Deep Learning Techniques to Enhance Blood Cell Detection in Patients with Leukemia by Mahwish Ilyas, Muhammad Bilal, Nadia Malik, Hikmat Ullah Khan, Muhammad Ramzan, Anam Naz

“…Early and accurate diagnosis is essential for detecting medical problems and then prescribing the most effective treatment strategies, especially in life-threatening diseases such as leukemia. …”
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Field Trial of Cluster Target Detection by Broadband Microwave Photonic MIMO Radar by Yuewen Zhou, Fangzheng Zhang, Jiayuan Kong, Yihan Wang, Jinhu Li, Kunyang Chen, Guanqun Sun, Yuhui He, Shilong Pan

“…Using a broadband digital beamforming algorithm that compensates for aperture fill time, precise target detection is achieved without beam squint and broadening problems. …”
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Machine learning applications for early detection of esophageal cancer: a systematic review by Farhang Hosseini, Farkhondeh Asadi, Hassan Emami, Rayan Ebnali Harari

“…However, the current literature is limited, and more studies are needed to investigate the clinical applications of these methods in early detection of EC. Furthermore, many studies suffer from class imbalance and biases, highlighting the need for validation of detection algorithms across organizations in longitudinal studies.…”
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A lightweight deep-learning model for parasite egg detection in microscopy images by Wenbin Xu, Qiang Zhai, Jizhong Liu, Xingyu Xu, Jing Hua

“…Automated detection can eliminate the dependence on professionals, but the current detection algorithms require large computational resources, which increases the lower limit of automated detection. …”
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Tensor RT optimized driver drowsiness detection system using edge device by Chandramohan Dhasarathan, Sambasivam Gnanasekaran, Arnab Pattanayak, Gourav Kumar, Kartik Vig, Vaibhav Narain, K.M. Deva Narayan, Sunidhi Garg

“…A reliable, non-invasive, and accurate technology that can detect and alert the driver in case of drowsiness, fatigue or distraction can help avert this rising problem. …”
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Universal Method for Detecting Violations in the Integrity of a Digital Image Based on Analysis of Blocks of its Matrix by Bobok I., Kobozeva A.

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An Optimization Coverage Strategy for Wireless Sensor Network Nodes Based on Path Loss and False Alarm Probability by Jianing Guo, Yunshan Sun, Ting Liu, Yanqin Li, Teng Fei

“…Ultimately, an optimization model for WSN coverage, based on combined detection probability, is developed and solved using an intelligent optimization algorithm. …”
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Mopidip: a modular real-time pipeline for machinery diagnosis and prognosis based on deep learning algorithms by Mattia Pujatti, Davide Calzà, Andrea Gobbi, Piergiorgio Svaizer, Marco Cristoforetti

“…In the age of the digital industry, Artificial Intelligence (AI)-based data-driven condition monitoring is proving extremely effective in detecting potential issues before they escalate into major problems, thereby reducing downtime, minimizing maintenance costs, and extending the lifespan of the equipment. …”
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Environmental Monitoring Smart System with Self-Sustaining Wireless Sensor Network Using Data Validation Algorithms by Kanwal T., Altaf S., Javed M. K.

“…However, our research identifies multiple faults, namely spike fault, out of range fault, outliers, and stuck at fault using a hybrid form of an algorithm. A comparison with the existing algorithm shows that the proposed algorithm improved data validation by 97 % in detecting multiple data faults using Artificial Intelligence techniques.…”
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Transportation Mode Detection Using Learning Methods and Self-Contained Sensors: Review by Ilhem Gharbi, Fadoua Taia-Alaoui, Hassen Fourati, Nicolas Vuillerme, Zebo Zhou

“…Due to increasing traffic congestion, travel modeling has gained importance in the development of transportion mode detection (TMD) strategies over the past decade. Nowadays, recent smartphones, equipped with integrated inertial measurement units (IMUs) and embedded algorithms, can play a crucial role in such development. …”
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Real-Time Human Ear Detection Based on the Joint of Yolo and RetinaFace by Huy Nguyen Quoc, Vinh Truong Hoang

“…As a complete identification system requires an effective detector for real-time application, and the current richness and variety of ear detection algorithms are poor due to the small and complex shape of human ears. …”
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Research Progress on Techniques for Quantitative Detection of Starch in Food in the Past Five Years by Xiao Wei, Fang Li, Yinfeng Liu, Song Li, Yachao Liu, Daming Dong

“…Their problems in real sample detection (e.g., time-consuming, cumbersome operation, over-reliance on modeling algorithms, etc.) were analyzed. …”
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