This guide outlines a detailed process for setting up the hardware, configuring the software, and implementing Python-based object detection, counting, and positional tracking. By using pre-built ...

ABSTRACT: One of the most basic and difficult areas of computer vision and image understanding applications is still object detection. Deep neural ... techniques. Using an innovative training regimen ...

To achieve autonomous and intelligent sampling of the hydrothermal plume by using AUV ... plume detection. This paper proposes a real-time object detection model for deep-sea hydrothermal plumes based ...

Korea have now developed a smart IoT-enabled end-to-end system for 3D object detection in real time based on deep learning and specialized for autonomous driving situations. "For autonomous ...

Microsoft researchers have been working on a deep-learning model that was trained ... "In our case, we aim to train a bug detection model without using training data from real-life bugs," they ...

YOLOv3’s report indicated it was capable of performing at detecting objects in 2018. The YOLOv3 framework builds the convolutional neural network called DarkNet-53, using ... workflow. From our point ...

Object detection is used in many different domains, including autonomous driving, video surveillance, and healthcare. In this post, I will briefly review the deep learning architectures that ...