The rise in visual dataset generation has necessitated the recent advancements in the field
of Deep Neural Networks (DNNs). Application domains like biomedical imaging require a …

Abstract Convolutional Neural Networks (CNNs) require highly parallel Hardware (HW)
accelerators in the form of Graphical Processing Units (GPUs), Application Specific …

A plethora of image and video-related applications involve complex processes that impose
the need for hardware accelerators to achieve real-time performance. Among these, notable …

Convolutional Neural Networks (CNNs) are a very popular class of artificial neural networks.
Current CNN models provide remarkable performance and accuracy in image processing …

Abstract Convolutional Neural Network (CNN) has been extensively used for image
recognition due to its great accuracy. This accuracy is achieved through emulating the optic …

The development of Convolutional Neural Network (CNN) contributes to breakthroughs
made in the field of artificial intelligence. Compared with traditional algorithms, CNN has …

Convolutional neural networks (CNNs) based deep learning algorithms require high data
flow and computational intensity. For real-time industrial applications, they need to …

Convolutional Neural Network (CNN) is the state-of-the-art deep learning approach used in
various computer vision algorithms due to their high accuracy. To ensure programmable …

Convolutional neural networks (CNNs) have dominated image recognition and object
detection models in the last few years. They can achieve the highest accuracies with several …

Due to recent advances in digital technologies, and availability of credible data, an area of
artificial intelligence, deep learning, has emerged and has demonstrated its ability and …