In the field of international trade, due to its wide range and complex interest relations, it is necessary to synthesize various information for analysis and decision-making. However, traditional data processing metho...
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This research explores the application of combined machine learning techniques for predicting disease symptoms, aiming to support early diagnosis and improve healthcare outcomes. By analyzing both regression and class...
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The ability to discern between text produced by artificial intelligence (AI) and that created by humans has become a crucial challenge in domains including academia, media, and digital communications due to the increa...
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With the development of technology and social progress, artificial intelligence (AI) has gradually penetrated into various fields of our lives. In the field of education, the application of AI is becoming increasingly...
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This paper focuses on the application of image classification in forest fire detection using unmanned aerial vehicles (UAVs), discussing the development history of UAV image classification and the significance of mach...
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ISBN:
(纸本)9798350352634;9798350352627
This paper focuses on the application of image classification in forest fire detection using unmanned aerial vehicles (UAVs), discussing the development history of UAV image classification and the significance of machine vision in fire monitoring. Initially, the dataset used for fire detection and the data processing and enhancement techniques are introduced. Subsequently, the construction and architecture of the image classification model are detailed. The core of this study is to enhance the accuracy of model image recognition in complex forest environments by replacing optimizers, modifying the model architecture, and adding modules. Various models and optimizers are compared and analyzed, and the operations and significance of enhancement methods and attention mechanisms are explored. The aim is to improve training effectiveness through these strategies, thereby effectively supporting UAVs in forest fire detection.
Traditional optimization analysis of electrical equipment in transmission engineering is often based on experience and rules, lacking intelligent methods. This leads to limitations in the adaptability and effectivenes...
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Heart attacks and hypertension are two cardiovascular disease risk factors that have a major impact on the microvascular system39;s structure and function. Fundus camera images can detect abnormalities in retinal bl...
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This study tackles mobile robots39; environmental perception challenges in complexity, presenting an advanced Visual-Inertial SLAM (VSLAM) technique that enhances accuracy, robustness, and real-time functionality. I...
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ISBN:
(纸本)9798350352634;9798350352627
This study tackles mobile robots' environmental perception challenges in complexity, presenting an advanced Visual-Inertial SLAM (VSLAM) technique that enhances accuracy, robustness, and real-time functionality. It bolsters visual odometry with ORB features for meticulous matching and selects keyframes, integrating IMU data for robust motion handling in low-textured scenes. Rear-end operations employ graph optimization and a bag-of-words-based loop closure, utilizing sliding window optimization and marginalization to curb accumulative errors, ensuring trajectory and map consistency. Experiments on KITTI, EuRoC, and TUM datasets surpass conventional methods like ORB-SLAM2 and VINS-Mono, trimming trajectory and mapping inaccuracies by 23.8% and 41.7%, respectively, with robust adaptability across motion modes and environments. System module timing analysis paves the way for real-time deployment on less powerful hardware. Future research directions include direct visual odometry, dynamic environment adaptation, multi-sensor fusion, and large-scale scene comprehension, pushing SLAM's frontier in intricate dynamics and empowering autonomous robot navigation.
Mobile banking has huge potentials to promote financial inclusions, especially in the rural areas. However, the adoptions in these areas are hampered by factors relating to security, misunderstanding, limitation in te...
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Intracranial Hemorrhage (ICH) is a critical medical condition characterized by bleeding within the skull, specifically in the brain. Timely detection and accurate classification of ICH from computed tomography (CT) sc...
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