Deep tech; Here’s how deep learning helps computers detect objects From autonomous driving to healthcare, object detection is used for many things ...

Learn about the advantages and disadvantages of cross-entropy, IoU, focal loss, and GIoU for object detection in deep learning. Agree & Join LinkedIn ...

YOLO (You Only Look Once) is an advanced deep learning software framework for object detection that can process an image in just one run, and consequently, this improves efficiency.

In this post, I will briefly review the deep learning architectures that help computers detect objects. Convolutional neural networks. One of the key components of most deep learning–based ...

YOLO v4[1] is a popular single stage object detector that performs detection and classification using CNNs. In this repository we use Complex-YOLO v4[2] approach, which is a efficient method for Lidar ...

These models behave differently in network architecture, training strategy, and optimization function. In this paper, we provide a review of deep learning-based object detection frameworks. Our review ...

In this project, a deep learning-based approach is used for lane detection on semi-urban roads. The proposed model consists of two main components: a CNN architecture, ResNet101, for semantic ...

As a major breakthrough in artificial intelligence, deep learning has achieved impressive success on solving grand challenges in many fields including speech recognition, natural language processing, ...

Bolstering the safety of self-driving cars with a deep learning-based object detection system. ScienceDaily. Retrieved May 13, 2025 from www.sciencedaily.com / releases / 2022 / 12 / 221212140800.htm.

There are many more potentially valuable applications for deep learning object detection in SMT and semiconductor applications that we are actively pursuing. For more information about this ...