Recent advancements in deep learning architecture have increased its utility in real-life
applications. Deep learning models require a large amount of data to train the model. In …

The aim of this systematic literature review (SLR) is to identify and critically evaluate current
research advancements with respect to small data and the use of data augmentation …

The deep learning methods based on convolutional neural network (CNN) have been
widely explored in dataset augmentation and recognition of plant leaf diseases. The recently …

In recent years, due to the shortage of timber resources, it has become necessary to reduce
the excessive consumption of forest resources. Non-destructive testing technology can …

Environmental sounds are being used widely in our lives. It is especially used in tasks such
as managing smart cities, location determination, surveillance systems, machine hearing …

Automatic environmental sound classification (ESC) is one of the upcoming areas of
research as most of the traditional studies are focused on speech and music signals …

Deep learning can be used for audio signal classification in a variety of ways. It can be used
to detect and classify various types of audio signals such as speech, music, and …

Forest ecosystems are of paramount importance to the sustainable existence of life on earth.
Unique natural and artificial phenomena pose severe threats to the perseverance of such …

Class imbalance is a key issue affecting the performance of computer vision applications
such as medical image analysis, objection detection and recognition, image segmentation …

Honey bees are one of the most important insects on the planet since they play a key role in
the pollination services of both cultivated and spontaneous flora. Recent years have seen an …