This research studied the effect of variations in a sensor's F lambda/d metric value (FLD) on the performance of machine learning algorithms such as the YOLO (You Only Look Once) algorithm for object classificatio...
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This research studied the effect of variations in a sensor's F lambda/d metric value (FLD) on the performance of machine learning algorithms such as the YOLO (You Only Look Once) algorithm for object classification. The YOLO_v3 and YOLO_v10 algorithms were trained using static imagery provided in the commonly available training dataset provided by Teledyne FLIR systems. imageprocessing techniques were used to degrade image quality of the test dataset also provided by Teledyne FLIR systems, simulating detector-limited to optics-limited performance, which results in a variation of the FLD metric between 0.339 and 7.98. The degraded test set was used to evaluate the performance of YOLO_v3 and YOLO_v10 for object classification and relate the FLD metric to the probability of detection. Results of YOLO_v3 and YOLO_v10 are presented for the varying levels of image degradation. A summary of the results is discussed along with recommendations for evaluating an algorithm's performance using a sensor's FLD metric value. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.
This research paper explores the application of singular value decomposition (SVD) in quantum imageprocessing (QIP), specifically focusing on the computation of eigenvalues using variational quantum algorithms. SVD i...
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With the continuous development of digital imageprocessingalgorithms, its application scenarios have been integrated from the simple research of a single image and a single algorithm to a multi-algorithm fusion anal...
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The world economy is threatened by counterfeit currencies. Counterfeit currencies are often difficult, time-consuming and ineffective to identify manually. Automated methods based on imageprocessing techniques and ma...
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For the purpose of reducing financial losses and environmental impacts, food waste detection is essential. Inorder to detect food waste using imageprocessing, this study investigates the efficiency of several machine...
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National traditional culture and traditional technology are the products of historical precipitation and indispensable precious resources. The establishment of national cultural database is of great significance for t...
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Medical image segmentation plays a pivotal role in computer-aided diagnosis by facilitating the extraction of essential features necessary for disease detection and treatment strategies. The continuous progress in ima...
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In order to comply with the trend of intelligent visual communication, this study proposed an innovative visual communication scenario based on imageprocessingalgorithms. The framework aims to optimize traditional k...
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Computer vision, driven by artificial intelligence, has become pervasive in diverse applications such as self-driving cars and law enforcement. However, the susceptibility of these systems to attacks has raised signif...
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作者：
Wanjari, KetanVerma, Prateek
Department of Computer Science and Engineering Faculty of Engineering and Technology Maharashtra Wardha442001 India
Department of Artificial Intelligence and Data Science Faculty of Engineering and Technology Maharashtra Wardha442001 India
Modern image recognition has experienced dramatic improvements because of Machine Learning and Deep Learning algorithms together. This study investigates CNNs and SVMs for recognition enhancement while reviewing image...
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