The article discusses the importance of explainable AI in understanding the decision-making process of deep neural networks. It highlights the need for engineers to…
Browsing: Deep Neural Networks
This article discusses the use of a modified STPN unit to estimate energy consumption in multi-functional hardware synapses for deep neural networks. The unit…
Researchers are planning to accelerate the development of artificial general intelligence (AGI) with a worldwide network of powerful computers. The first supercomputer will come…
Scientists are working to accelerate the development of artificial general intelligence (AGI) by creating a worldwide network of powerful supercomputers. These supercomputers will be…
This Special Issue focuses on the use of machine learning algorithms in image understanding and analysis. Topics of interest include deep neural networks, graph-based…
SQUID is a genomic DNN interpretability framework that utilizes domain-specific surrogate modelling to improve the understanding of underlying biological mechanisms in deep neural networks.…
The article discusses the vulnerability of machine learning methods, particularly deep neural networks, to adversarial attacks. These attacks can drastically affect the accuracy of…
This article discusses the two popular models in the field of artificial intelligence, Large Language Models (LLM) and Generative AI, and their impact on…
YOLOv10 is an improved version of the popular object detection algorithm, YOLO, offering faster processing speed and higher accuracy. It uses a “one-stage” approach…
This article discusses the use of deep neural networks (DNNs) and a novel data augmentation method based on generative adversarial networks (GANs) to improve…