In recent years, deep learning algorithms have rapidly revolutionized artificial intelligence,
particularly machine learning, enabling researchers and practitioners to extend previously …

An enormous number of CNN classification algorithms have been proposed in the literature.
Nevertheless, in these algorithms, appropriate filter size selection, data preparation …

We demonstrate that neural networks that process noisy data can learn to exploit, when
available, access to auxiliary noise that is correlated with the noise on the data. In effect, the …

Recent research in convolutional neural network (CNN) has provided a variety of new
architectures for deep learning. One interesting new architecture is the local binary …

In this paper, we present a novel U-module for better parameters initialization of
convolutional neural network (CNN) on medical image classification tasks. CNN-based …

The motivation behind our work is to improve commuters overall train ride experience by
providing crowd density information of incoming trains. Given the incoming train information …

Research publications reflect advancements in the corresponding research domain. In these
research publications, scientists often use citations to bolster the presented research …

Image noise detection is one of the most challenging aspect in the field of image processing
and analysis. Generally, the noise affects the information of image, especially when the …

Image classification entails assigning labels to an image based on its visual representation.
Among the approaches used for this problem, the use of neural networks is particularly …

Color machine vision is a riveting technology crucial in pioneering innovations like
autonomous vehicles, autonomous drone deliveries, automated stores, robots, infrastructure …