Crop counting is a crucial step in crop yield estimation. By counting, crop growth status can
be accurately detected and adjusted, improving crop yield and quality. In recent years, with …

The development of safety-oriented research and applications requires fine-grain vehicle
trajectories that not only have high accuracy, but also capture substantial safety-critical …

Recently, due to the excellent representation ability of convolutional neural networks
(CNNs), object detection in remote sensing images has undergone remarkable …

In this paper, we study teacher-student learning from the perspective of data initialization
and propose a novel algorithm called Active Teacher for semi-supervised object detection …

Achieving a reliable LiDAR-based object detector in autonomous driving is paramount, but
its success hinges on obtaining large amounts of precise 3D annotations. Active learning …

This paper proposes a scalable technique for developing lightweight yet powerful models for
object detection in videos using self-training with knowledge distillation. This approach …

Despite the huge success of object detection, the training process still requires an immense
amount of labeled data. Although various active learning solutions for object detection have …

We propose a novel semi-supervised active learning framework for monocular 3D object
detection with LiDAR guidance (MonoLiG), which leverages all modalities of collected data …

As an important data selection schema, active learning emerges as the essential component
when iterating an Artificial Intelligence (AI) model. It becomes even more critical given the …

Unmanned aerial vehicles (UAVs) are widely used for image acquisition in various
applications, and object detection is a crucial task for UAV imagery analysis. However …