Abstract: Convolutional neural networks (CNNs) have established themselves as the industry standard for image classification jobs. Convolutional neural network architectures have been created and ...

Abstract: With the rapid advancement of wearable devices and Internet of Things (IoT) technologies, sensor data generated by edge devices has surged. This data is crucial for advancing IoT ...

Abstract: With the rapid advancement of remote sensing technology, change detection using bitemporal remote sensing images has significant applications in land use planning and environmental ...

Abstract: In the field of Internet of Things (IoT), uncrewed aerial vehicle (UAV) swarms are widely used to assist IoT communication due to their simple deployment, high mobility and high cost ...

Abstract: In this work, we propose a learning-based one-stage planner for trajectory generation of quadrotor in obstacle-cluttered environment without relying on explicit map. We integrate perception ...

Abstract: Motor imagery (MI) decoding is the basis of external device control via electroencephalogram (EEG). However, the majority of studies prioritize enhancing the accuracy of decoding methods, ...

Abstract: As data mining & analytics technologies advance, they offer unprecedented opportunities for extracting valuable insights from vast datasets. However, these advancements bring forth a complex ...

Abstract: UAV-assisted MEC revolutionizes edge computing by deploying UAVs for real-time data processing in areas lacking infrastructure, supporting a wide range of applications from emergency ...

Abstract: Path planning is an important step in ensuring the safety of unmanned surface vehicle (USV) navigation and executing missions quickly and efficiently. However, current USV path planning ...

Abstract: Infrared small target (IRST) detection aims at separating targets from cluttered background. Although many deep learning-based single-frame IRST (SIRST) detection methods have achieved ...

Abstract: Artificial intelligence (AI) image generation powered by large language model (large language modelss (LLMs)) enables highly realistic image synthesis and manipulation, posing significant ...

Abstract: Leveraging the extensive training data from SA-1B, the segment anything model (SAM) demonstrates remarkable generalization and zero-shot capabilities. However, as a category-agnostic ...