Image augmentation is a common mechanism to alleviate data scarcity in image
classification. Existing image augmentation methods consist of two categories. Perturbation …

In contemporary machine learning, enhancing model generalization through diversified
datasets is essential. Yet, collecting additional data often faces prohibitive costs and privacy …

Deep neural networks (DNNs) have heavily relied on traditional computational units like
CPUs and GPUs. However, this conventional approach brings significant computational …

Vehicle Make and Model Recognition (MMR) systems provide a fully automatic framework to
recognize and classify different vehicle models. Several approaches have been proposed to …

Real-time Digital Twinning of physical world scenes onto the Metaverse is necessary for a
myriad of applications such as augmented-reality (AR) assisted driving. In AR assisted …

In this paper, we propose a locally enhanced PCANet neural network for fine-grained
classification of vehicles. The proposed method adopts the PCANet unsupervised network …

This paper presents a method that enables detecting multiple mutually exclusive features of
each class using the same convolutional neural network (CNN). This method proposes the …

The straightforward task of working with objects that fall under several intra-class categories
inside the same inter-class category group, such as various bird species or various motor …

Recognition of objects with subtle differences has been used in many practical applications,
such as car model recognition and maritime vessel identification. For discrimination of the …