Iterative Assessment of Edge Criticality: Efficiency Enhancement or Hidden Insufficiency Detection by Vasily Lubashevskiy, Hamza Ejjbiri, Ihor Lubashevsky

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Optimized Machine Learning for the Early Detection of Polycystic Ovary Syndrome in Women by Bharti Panjwani, Jyoti Yadav, Vijay Mohan, Neha Agarwal, Saurabh Agarwal

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Objective Assessment of Cancer Biomarkers Using Semi-Rare Event Detection by Jeroen A. W. M. van der Laak, Albertus G. Siebers, Sabine A. A. P. Aalders, Johanna M. M. Grefte, Peter C. M. de Wilde, Johan Bulten

“…Objective and reproducible assessment of cancer biomarkers may be performed using rare event detection systems. Because many biomarkers are not true ‘rare events’, in this study a semi-rare event detection system was developed. …”
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PREVALENCE AND EFFECTIVENESS OF DETECTING GASTROINTESTINAL DISORDERS ASSOCIATED WITH CHRONIC FATIGUE IN SEAMEN by Olexandr M. Ignatiev, Oleksij I. Paniuta, Tetiana L. Prutiian

“…Underdiagnosis is associated with both symptom relief during the period between trips and the non-disclosure of seamen's complaints. The organizational features of the work of the medical commission exclude a possibility of primary detection of peptic ulcer and irritable bowel syndrome in seamen.…”
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ELNet: An Efficient and Lightweight Network for Small Object Detection in UAV Imagery by Hui Li, Jianbo Ma, Jianlin Zhang

“…To address this issue, we propose ELNet, an efficient and lightweight object detection model based on YOLOv12n. First, based on an analysis of UAV image characteristics, we strategically remove two A2C2f modules from YOLOv12n and adjust the size and number of detection heads. …”
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Advanced machine learning techniques for social support detection on social media by Olga Kolesnikova, Moein Shahiki Tash, Zahra Ahani, Ameeta Agrawal, Raúl Monroy, Grigori Sidorov

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Breast Cancer Detection Using Mammography: Image Processing to Deep Learning by Shahzad Ahmad Qureshi, Aziz-Ul-Rehman, Lal Hussain, Touseef Sadiq, Syed Taimoor Hussain Shah, Adil Aslam Mir, Muhammad Amin Nadim, Darnell K. Adrian Williams, Tim Q. Duong, Qurat-Ul-Ain Chaudhary, Natasha Habib, Asrar Ahmad, Syed Adil Hussain Shah

“…Large-scale datasets required for a broader and in-depth analysis of novel methods for breast cancer detection are also discussed in this article. …”
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Automatic detection and visualization of temporomandibular joint effusion with deep neural network by Yeon-Hee Lee, Seonggwang Jeon, Jong-Hyun Won, Q.-Schick Auh, Yung-Kyun Noh

“…The Grad-CAM visualizations agreed with the model learned through important features in the TMJ area, particularly around the articular disc. …”
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Lightweight obstacle detection for unmanned mining trucks in open-pit mines by Guangwei Liu, Jian Lei, Zhiqing Guo, Senlin Chai, Chonghui Ren

“…Abstract This paper aims to solve the problem of the difficulty in balancing the model size and detection accuracy of the unmanned mining truck detection network in open-pit mines, as well as the problem that the existing model is not suitable for mining truck equipment. …”
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CFR-YOLO: A Novel Cow Face Detection Network Based on YOLOv7 Improvement by Guohong Gao, Yuxin Ma, Jianping Wang, Zhiyu Li, Yan Wang, Haofan Bai

“…In order to solve these problems, this study explores the application of cattle face detection technology in cattle individual detection to improve the accuracy of detection, an approach that is particularly important in smart animal husbandry and animal behavior analysis. …”
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Advanced Non-Unit Protection Strategy for MMC-HVDC Grids Leveraging Two-Dimensional High-Frequency Characteristics via HHT and SVM by Chenglin Ren, Yige Hu, Xiang Lu, Yue Chen, Kepeng Xia, Hailin Li

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University Media Content Detection and Classification Based on Information Fusion Algorithm by Shuntao Zhang, Qinglan Yu, Tianming Yang, Kai Peng

“…This essay mainly introduces the technology of university media content detection and classification based on information fusion algorithm and focuses on the application of university multimedia content detection, analysis, and understanding, to explore the image discrimination auxiliary attribute feature learning and content association prediction and classification. …”
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Incorporating exon–exon junction reads enhances differential splicing detection by Mai T. Pham, Michael J. G. Milevskiy, Jane E. Visvader, Yunshun Chen

“…This DEJU analysis workflow adopts a new feature quantification approach that jointly summarises exon and exon–exon junction reads, which are then integrated into the established Rsubread-edgeR/limma frameworks. …”
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Structural Fault Detection and Diagnosis for Combine Harvesters: A Critical Review by Haiyang Wang, Liyun Lao, Honglei Zhang, Zhong Tang, Pengfei Qian, Qi He

“…Subsequently, it details the core steps of data-driven methods, including the acquisition of operational data from various sensors (e.g., vibration, acoustic, strain), signal preprocessing methods, signal processing and feature extraction techniques covering time-domain, frequency-domain, time–frequency domain combination, and modal analysis among others, and the use of machine learning and artificial intelligence models for fault pattern learning and diagnosis. …”
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Plant leaf disease detection using vision transformers for precision agriculture by Murugavalli S, Gopi R

“…In leaf image analysis, convolutional neural networks (CNNs) have revealed promise in leaf disease detection and classification. …”
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Detection of multiple pesticide residues on the surface of broccoli based on hyperspectral imaging by GUI Jiangsheng, GU Min, WU Zixian, BAO Xiao’an

“…To increase efficiency of the model and reduce the redundancy of the hyperspectral image, using the principal component analysis (PCA) algorithm and successive projection algorithm (SPA) for feature extraction. …”
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Automated Detection of Poor-Quality Scintigraphic Images Using Machine Learning by Anil K. Pandey, Akshima Sharma, Param D. Sharma, Chandra S. Bal, Rakesh Kumar

“…The principal component analysis (PCA) of all the images was performed and the first 32 principal components (PCs) were retained as feature vectors of the image. …”
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Leveraging stacking machine learning models and optimization for improved cyberattack detection by Neha Pramanick, Jimson Mathew, Shitharth Selvarajan, Mayank Agarwal

“…Abstract The ever-growing number of complex cyber attacks requires the need for high-level intrusion detection systems (IDS). While the available research deals with traditional, hybrid, and ensemble methods for network data analysis, serious challenges are still being met in terms of producing robust and highly accurate detection systems. …”
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A method for synthetic speech detection using local phase quantization by Jia XU, Zhihua JIAN, Honghui JIN, Man YANG

“…Due to the convenience of speech synthesis, synthesized disguised speech poses a great threat to the security of speaker verification systems.In order to further enhance the ability of detecting the camouflage to the speaker verification system, a method of synthetic speech detection was put forward using the information in spectral domain of the synthetic speech spectrogram.The method employed the local phase quantization (LPQ) algorithm to describe frequency domain information in the speech spectrogram.Firstly, the spectrogram was divided into several sub-blocks, and then the LPQ was performed on each sub-block.After the histogram statistical analysis, the LPQ feature vector was obtained and used as the input feature of the random forest classifier to realize the synthetic speech detection.The experimental results demonstrate that the proposed method further reduces tandem detection cost function (t-DCF) and has better generalization ability.…”
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Image saliency detection in wavelet domain based on the contrast sensitivity function by Ying-chun GUO, Yan-hong FENG, Gang YAN, Ming YU

“…A method of high definition saliency detection based on contrast sensitive function and wavelet analysis was proposed in order to improve the resolution of saliency maps.Original image was filtered by contrast sensitive function in YCbCr space,which could simulate the contrast of human eyes; then wavelet decomposition was carried out in Y,Cb,and Cr three channels individually,low frequency and high frequency feature saliency maps were extracted and further combined to obtain saliency map in single channel; finally saliency maps in three channels were fused to the high resolution saliency map.Experiments result show that the saliency images have high resolution,well-defined boundaries,and whole highlight salient objects.…”
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