The most significant technical challenges of current aerial image object-detection tasks are
the extremely low accuracy for detecting small objects that are densely distributed within a …

Natural breeding scenes have the characteristics of a large number of cows, complex
lighting, and a complex background environment, which presents great difficulties for the …

Deep learning-based methods for detecting surface defects on strip steel have advanced
detection capabilities, but there are still problems of target loss, false alarms, large …

In recent years, the realm of deep learning has witnessed significant advancements,
particularly in object detection algorithms. However, the unique challenges posed by remote …

Forests are the most important part of terrestrial ecosystems. In the context of China's
industrialization and urbanization, mining activities have caused huge damage to the forest …

Object detection in unmanned aerial vehicle (UAV) images is an extremely challenging task
and involves problems such as multi-scale objects, a high proportion of small objects, and …

Introduction Efficiently and precisely identifying tomatoes amidst intricate surroundings is
essential for advancing the automation of tomato harvesting. Current object detection …

Automatic pavement crack detection is crucial for reducing road maintenance costs and
ensuring transportation safety. Although convolutional neural networks (CNNs) have been …

With the advantages of simple model structure and performance-speed balance, the single
object tracking (SOT) model based on a Transformer has become a hot topic in the current …

The growth environment of green walnuts is complex. In the actual picking and identification
process, interference from near-background colors, occlusion by branches and leaves, and …