Abstract: This paper presents the first discrete-time distributed algorithm to track the tightest ellipsoids that outer approximates the global dynamic intersection of ellipsoids. Given an undirected ...

Abstract: Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex ...

Abstract: The trajectory planning of multiple unmanned aerial vehicles (UAVs) is the core of efficient UAV mission execution. Existing studies have mainly transformed this problem into a ...

Abstract: Modern day cellular mobile networks use Massive MIMO technology to extend range and service multiple devices within a cell. This has brought tremendous improvements in the high peak data ...

Abstract: In the field of multisource remote sensing image classification, remarkable progress has been made by using the convolutional neural network (CNN) and Transformer. While CNNs are constrained ...

Abstract: In Artificial Intelligence, there is an increasing demand for adaptive models capable of dealing with a diverse spectrum of learning tasks, surpassing the limitations of systems devised to ...

Abstract: Regarding the current problems of false alarms and missed detections in fire detection, we propose a high-precision fire detection algorithm, YOLOV9-CBM (C3-SE, BiFPN, MPDIoU), by optimizing ...

Abstract: Nivedita Arora: Collecting real-time, granular environmental data is essential for urban health, agriculture, and disaster prevention. However, it must be done sustainably, with minimal ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=9944983 ...

Abstract: In hyperspectral images (HSIs), different land cover (LC) classes have distinct reflective characteristics at various wavelengths. Therefore, relying on only a few bands to distinguish all ...

Abstract: Deep hashing has been widely used in image retrieval tasks, while deep hashing networks are vulnerable to adversarial example attacks. To improve the deep hashing networks’ robustness, it is ...