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Priyank Kalgaonkar and Mohamed El-Sharkawy
Accurate perception is crucial for autonomous vehicles (AVs) to navigate safely, especially in adverse weather and lighting conditions where single-sensor networks (e.g., cameras or radar) struggle with reduced maneuverability and unrecognizable targets....
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Majdi Sukkar, Madhu Shukla, Dinesh Kumar, Vassilis C. Gerogiannis, Andreas Kanavos and Biswaranjan Acharya
Effective collision risk reduction in autonomous vehicles relies on robust and straightforward pedestrian tracking. Challenges posed by occlusion and switching scenarios significantly impede the reliability of pedestrian tracking. In the current study, w...
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Jerry Gao, Charanjit Kaur Bambrah, Nidhi Parihar, Sharvaree Kshirsagar, Sruthi Mallarapu, Hailong Yu, Jane Wu and Yunyun Yang
With the development of artificial intelligence, the intelligence of agriculture has become a trend. Intelligent monitoring of agricultural activities is an important part of it. However, due to difficulties in achieving a balance between quality and cos...
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Andrea Settimi, Naravich Chutisilp, Florian Aymanns, Julien Gamerro and Yves Weinand
We present TimberTool (TTool v2.1.1), a software designed for woodworking tasks assisted by augmented reality (AR), emphasizing its essential function of the real-time localization of a tool head?s poses within camera frames. The localization process, a ...
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Julio-Alejandro Romero-González, Diana-Margarita Córdova-Esparza, Juan Terven, Ana-Marcela Herrera-Navarro and Hugo Jiménez-Hernández
This paper introduces a novel background subtraction method that utilizes texture-level analysis based on the Gabor filter bank and statistical moments. The method addresses the challenge of accurately detecting moving objects that exhibit similar color ...
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Ali Dorosti, Ali Asghar Alesheikh and Mohammad Sharif
Advancements in navigation and tracking technologies have resulted in a significant increase in movement data within road networks. Analyzing the trajectories of network-constrained moving objects makes a profound contribution to transportation and urban...
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Hy Nguyen, Srikanth Thudumu, Hung Du, Kon Mouzakis and Rajesh Vasa
Several approaches have applied Deep Reinforcement Learning (DRL) to Unmanned Aerial Vehicles (UAVs) to do autonomous object tracking. These methods, however, are resource intensive and require prior knowledge of the environment, making them difficult to...
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Jose Antonio Carballo, Javier Bonilla, Jesús Fernández-Reche, Bijan Nouri, Antonio Avila-Marin, Yann Fabel and Diego-César Alarcón-Padilla
Due to the need to know the availability of solar resources for the solar renewable technologies in advance, this paper presents a new methodology based on computer vision and the object detection technique that uses convolutional neural networks (Effici...
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Tingbo Xie and Xifan Yao
An approach for object tracking in logistics warehouses based on YOLOv5 and DeepSORT is proposed, which distinguishes humans from goods, and an evaluation system is established for object tracking in logistics warehouse scenarios.
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Zongxiang Liu, Chunmei Zhou and Junwen Luo
The random finite set (RFS) approach for multi-target tracking is widely researched because it has a rigorous theoretical basis. However, many prior parameters such as the clutter density, survival probability and detection probability of the target, pru...
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