Owing to effective and flexible data acquisition, unmanned aerial vehicles (UAVs) have
recently become a hotspot across the fields of computer vision (CV) and remote sensing …

One of the main challenges in machine vision relates to the problem of obtaining robust
representation of visual features that remain unaffected by geometric transformations. This …

Deep learning-based plant disease detection has gained significant attention from the
scientific community. However, various aspects of real horticultural conditions have not yet …

The cost-effectiveness, compact size, and inherent flexibility of UAV technology have
garnered significant attention. Utilizing sensors, UAVs capture ground-based targets …

Limited training data, high dimensionality, image complexity, and similarity between classes
are challenges confronting hyperspectral image (HSI) classification often resulting in …

Automated visual stimuli evoked multi-channel electroencephalograph (EEG) signals
classification is in a nascent stage but is receiving progressive attention from researchers …

Scarcity of labeled data in sensitive research areas such as healthcare limits the
performance of artificially intelligent (AI) models. The effort required in labeling the acquired …

With the advances in remote sensing, wild animals sprawling over a vast area can be easily
and quickly captured using low-cost unmanned aerial vehicle imagery. We propose an …

At present times, indoor surveillance becomes a hot research topic among researchers and
business sectors. Human detection is one of the vital areas of focus in the surveillance …

The identification of mineral deposit footprints by processing geochemical survey data
constitutes a crucial stage in mineral exploration because it provides valuable and …