The field of machine learning has taken a dramatic twist in recent times, with the rise of the
Artificial Neural Network (ANN). These biologically inspired computational models are able …

CNNs have rapidly become state-of-the-art frameworks for various applications used in
image classification. We typically need big, ground-based training data set so as to use …

With the increase of the Artificial Neural Network (ANN), machine learning has taken a
forceful twist in recent times. One of the most spectacular kinds of ANN design is the …

Convolutional neural networks (CNNs) have been applied to visual tasks since the late
1980s. However, despite a few scattered applications, they were dormant until the mid …

Computer vision has become increasingly important and effective in recent years due to its
wide-ranging applications in areas as diverse as smart surveillance and monitoring, health …

Convolutional Neural Networks (CNNs) are powerful models that achieve impressive results
for image classification. In addition, pre-trained CNNs are also useful for other computer …

Convolutional neural networks (CNNs) are one of the main types of neural networks used for
image recognition and classification. CNNs have several uses, some of which are object …

Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing
industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of …

One stop guide to implementing award-winning, and cutting-edge CNN architectures Key
Features Fast-paced guide with use cases and real-world examples to get well versed with …

This paper presents an empirical analysis of theperformance of popular convolutional neural
networks (CNNs) for identifying objects in real time video feeds. The most popular …