A Semiparametric Model for Hyperspectral Anomaly Detection by Dalton Rosario

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Orange Leaves Images Dataset for the Detection of Huanglongbing by Juan Carlos Torres-Galván, Paul Hernández Herrera, Juan Antonio Obispo, Xocoyotzin Guadalupe Ávila Cruz, Liliana Montserrat Camacho Ibarra, Paula Magaldi Morales Orosco, Alfonso Alba, Edgar R. Arce-Santana, Valdemar Arce-Guevara, J. S. Murguía, Edgar Guevara, Miguel G. Ramírez-Elías

“…The use of ML and DL for image classification in plant disease has generated significant interest due to their cost, automatization, scalability, and early detection. However, high-quality image datasets are required to train robust classifier models for plant disease detection. …”
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Automated Earthwork Detection Using Topological Persistence by Dana A. Lapides, Gillian Grindstaff, Mary H. Nichols

“…These tools are either labor‐intensive or require special pre‐processing or a priori assumptions about structures that limit generalizability. …”
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OCT angiography in detecting preclinical diabetic retinopathy by A. N. Stulova, N. S. Semenova, A. V. Zheleznyakova, V. S. Akopyan, D. V. Lipatov

“…Many studies evaluate vessel density in superficial and deep plexuses in these patients using different methods of image processing and different qualitative and quantitative parameters. …”
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Sensor-Based Detection of Characteristics of Rubber Springs by Leopold Hrabovský, Jan Blata, Ladislav Kovář, Michal Kolesár, Jaromír Štěpáník

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Automatic Detection of Defects Using Active Thermography by Miguel Gómez, David Castro

“…Finally, an automated method based on the Signal-to-Noise Ratio (SNR) value is implemented for defect detection, with which defects of a 5 mm diameter and a 3 mm depth can be detected. …”
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Cross-Modality Object Detection Based on DETR by Xinyi Huang, Guochun Ma

“…Cross-modality can integrate complementary information from different modalities to improve the reliability and robustness of object detection effectively. However, compared to processing uni-modality inputs, cross-modality may significantly increase the computational complexity of the model, which will lead to huge memory consumption. …”
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General Framework for Domain-Specialization of Stance Detection by Brodie Mather, Bonnie J Dorr, Owen Rambow, Tomek Strzalkowski

“…The notions purpose and function serve as natural constraints on the choice of belief categories during resource building which, in turn, constrains stance detection. We demonstrate that linguistic constraints (e.g., light verb processing) further refine the choice of predicate-argument pairings for belief and sentiment assignments, yielding significant increases in F1 score for stance detection over a strong baseline.…”
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Voice Detection Using Convolutional Neural Network by U. A. Vishniakou, B. H. Shaya

“…Thus, the system is able to detect the sound of a voice in a crowded public place, and there is no need for a sound separation phase for pre-processing, as other modern systems require. …”
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Lightweight Vehicle Detection Based on Mamba_ViT by Ze Song, Yuhai Wang, Shuobo Xu, Peng Wang, Lele Liu

“…Vehicle detection algorithms are essential for intelligent traffic management and autonomous driving systems. …”
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An Efficient Anomalous Sound Detection System for Microcontrollers by Yi-Cheng Lo, Tsung-Lin Tsai, Chieh-Wen Yang, An-Yeu Wu

“…Anomalous Sound Detection (ASD) systems are pivotal in the Industrial Internet of Things (IIoT). …”
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Detection of microfibres in wastewater sludge with deep learning by Félix Martí-Pérez, Ana Domínguez-Rodríquez, Carlos Monserrat, Cèsar Ferri, María-José Luján-Facundo, Eva Ferrer-Polonio, Amparo Bes-Piá, José-Antonio Mendoza-Roca

“…In particular, wastewater treatment plants are among the primary contributors to the release of MFi into ecosystems, making it crucial to detect and quantify these pollutants, mainly in sewage sludge. …”
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Video Anomaly Detection Methods: a Survey by WU Peichen, YUAN Lining, GUO Fang, LIU Zhao

“…Video abnormal behavior detection is a hot research topic in computer vision. …”
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Multimodal Ultrasonic Imaging for Breast Cancer Detection by Jorge CAMACHO, Luis MEDINA, Jorge F. CRUZA, Jose M. MORENO, Carlos FRITSCH

“…Such an arrangement is well suited for multi-modal imaging that includes reflectivity, compounded, tomography, and phase coherence images for increased specificity in breast cancer detection. Preliminary work carried out with a mechanical emulation of the ring array and a standard breast phantom shows a high resolution and contrast, with an artifact-free capability provided by phase coherence processing.…”
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Tuberculosis detection using few shot learning by Kamran Riasat, Akhtar Jamil, Shaha Al-Otaibi, Sania Zeb, Saima Riasat, Shamsa Kanwal

“…Moreover, TB-FSNet is designed for seamless integration into embedded devices, making it suitable for deployment on edge devises. The model processes Chest X-ray images in real-time, providing immediate confidence scores for disease detection. …”
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Improved model for intrusion detection in the Internet of Things by Marina S. Amine, Fayza A. Nada, Khalid M. Hosny

“…IoT has become more efficient in processing large amounts of data in less time than before because it does not require human intervention. …”
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Pupil Detection Algorithm Based on ViM by Yu Zhang, Changyuan Wang, Pengbo Wang, Pengxiang Xue

“…The experimental results demonstrate that the proposed ViMSA achieves 99.6% detection accuracy at five pixels with an RMSE of 1.67 pixels and a processing speed exceeding 100 FPS, meeting real-time monitoring requirements for various applications including operation under variable and uneven lighting conditions, assistive technology (enabling communication with neuro-motor disorder patients through pupil recognition), computer gaming, and automotive industry applications (enhancing traffic safety by monitoring drivers’ cognitive states).…”
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Motion detection for patient safety in CT scanner by Zaynab Boujelb, Ahmed Idrissi, Achraf Benba, El Mahjoub Chakir

“…It uses advanced image processing techniques to detect motion and stop the emission of X-rays from the machine as soon as the motion of the patient is detected. …”
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A review of deep learning in blink detection by Jianbin Xiong, Weikun Dai, Qi Wang, Xiangjun Dong, Baoyu Ye, Jianxiang Yang

“…Blink detection is a highly concerned research direction in the field of computer vision, which plays a key role in various application scenes such as human-computer interaction, fatigue detection and emotion perception. …”
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Conditions and factors affecting the accuracy of olfactometric detection by Petra Riedlova, Spiros Tavandzis, Josef Kana, Jaromir Roubec

“…After long-term observation, a qualitative analysis was performed and factors that may play a role in the early detection of the disease were listed. Results: The results of the search for the different factors have been compiled into two groups, focussing on the actual handling of the patient biological sample from collection, processing, storage until transport, preparation of the sample,and detection. …”
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