Autonomous vehicles (AVs) promise a future with safer, cleaner, more efficient, and more
reliable transportation. However, the current approach to autonomy has focused on building …

In order to reach the highest level of automation, autonomous vehicles (AVs) are required to
be aware of surrounding objects and detect them even in adverse weather. Detecting …

Object detection (OD) is crucial to autonomous driving. On the other hand, unknown objects,
which have not been seen in training sample set, are one of the reasons that hinder …

Reliable object detection using cameras plays a crucial role in enabling autonomous
vehicles to perceive their surroundings. However, existing camera-based object detection …

Chart comprehension presents significant challenges for machine learning models due to
the diverse and intricate shapes of charts. Existing multimodal methods often overlook these …

The Object detection, especially for autonomous navigation, requires high accuracy of the
localization accuracy on the objects detected. The bounding box is devised to provide the …

Despite the advancements in the development of autonomous vehicles (AVs), there are still
numerous complex situations in which AVs may encounter challenges. In recent years, the …

This study addresses the limitations of existing autonomous vehicle datasets, particularly the
need for greater specificity of weather conditions and road types. We utilized X-CAR to …

Traffic flow counting is an object detection problem. YOLO (" You Only Look Once") is a
popular object detection network. Spiking-YOLO converts the YOLO network from ANN …

Autonomous vehicles promise a future with a safer, cleaner, more efficient, and more
reliable transportation system. However, the current approach to autonomy has focused on …