Deep learning models are widely being employed for object detection due to their high
performance. However, the majority of applications that require object detection are …

This study concentrates on deep learning-based lightweight object detection models on
edge devices. Designing such lightweight object recognition models is more difficult than …

Traffic video analytics has become one of the core components in the evolution of
transportation systems. Artificially intelligent traffic management systems apply computer …

Abstract Background and Objective At present, the COVID-19 epidemic is still spreading
worldwide and wearing a mask in public areas is an effective way to prevent the spread of …

Purpose: Visual perception enables robots to perceive the environment. Visual data is
processed using computer vision algorithms that are usually time-expensive and require …

Citrus fruit detection can provide technical support for fine management and yield
determination of citrus orchards. Accurate detection of citrus fruits in mountain orchards is …

Currently, the tuberculosis (TB) detection model based on chest X-ray images has the
problem of excessive reliance on hardware computing resources, high equipment …

Semantic segmentation of remote sensing images is always a critical and challenging task.
Graph neural networks, which can capture global contextual representations, can exploit …

Ship recognition and georeferencing using monitoring cameras are crucial to many
applications in maritime situational awareness. Although deep learning algorithms are …

The instance segmentation of traffic targets in complex road scenes is one of the most
challenging tasks in autonomous driving. Unlike the bounding box localization for object …