YOLO has become a central real-time object detection system for robotics, driverless cars,
and video monitoring applications. We present a comprehensive analysis of YOLO's …

The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI)
models is likely to usher in newfound capabilities in medicine. We propose a new paradigm …

Recent research on remote sensing object detection has largely focused on improving the
representation of oriented bounding boxes but has overlooked the unique prior knowledge …

In this paper, we aim to design an efficient real-time object detector that exceeds the YOLO
series and is easily extensible for many object recognition tasks such as instance …

Object detection is a significant downstream task in computer vision. For the on-board edge
computing platforms, a giant model is difficult to achieve the real-time detection requirement …

The success of the Segment Anything Model (SAM) demonstrates the significance of data-
centric machine learning. However, due to the difficulties and high costs associated with …

In-flight system failure is one of the major safety concerns in the operation of unmanned
aerial vehicles (UAVs) in urban environments. To address this concern, a safety framework …

Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI,
particularly machine learning algorithms, range from initial image processing to high-level …

Current state-of-the-art two-stage detectors generate oriented proposals through time-
consuming schemes. This diminishes the detectors' speed, thereby becoming the …

We present an open-source toolbox, named MMRotate, which provides a coherent algorithm
framework of training, inferring, and evaluation for the popular rotated object detection …