Autonomous vehicles require constant environmental perception to obtain the distribution of
obstacles to achieve safe driving. Specifically, 3D object detection is a vital functional …

In the realm of computer vision, Deep Convolutional Neural Networks (DCNNs) have
demonstrated excellent performance. Video Processing, Object Detection, Image …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

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 …

Reinforcement learning algorithms typically struggle in the absence of a dense, well-shaped
reward function. Intrinsically motivated exploration methods address this limitation by …

With the rapid advancements in the field of autonomous driving, the need for faster and more
accurate object detection frameworks has become a necessity. Many recent deep learning …

To understand the real world using various types of data, Artificial Intelligence (AI) is the
most used technique nowadays. While finding the pattern within the analyzed data …

In recent years, deep learning algorithms have rapidly revolutionized artificial intelligence,
particularly machine learning, enabling researchers and practitioners to extend previously …

Object detection for industrial applications refers to analyzing the captured images and
videos and finding the relationship between the detected objects for better optimization, data …

The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …