Crop production can be greatly reduced due to various diseases, which seriously endangers
food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional …

Deep learning models are widely being employed for object detection due to their high
performance. However, the majority of applications that require object detection are …

Road transport is the most prone to accidents, resulting in significant fatalities and injuries. It
also faces a plethora of never-ending problems, such as the frequent loss of lives and …

Addressing issues related to multi-label classification is relevant in many fields of
applications. In this work. We present a multi-label classification architecture based on Multi …

With the recent advances in the Internet of Things (IoT) technologies, various human-
centered applications have proliferated and improved the quality of users' life. In the …

This study concentrates on deep learning-based lightweight object detection models on
edge devices. Designing such lightweight object recognition models is more difficult than …

Wearable sensing technologies are having a worldwide impact on the creation of novel
business opportunities and application services that are benefiting the common citizen. By …

Cardiovascular diseases (CVDs) are a group of heart and blood vessel disorders that is one
of the most serious dangers to human health, and the number of such patients is still …

With the growth of real-time and latency-sensitive applications in the Internet of Everything
(IoE), service placement cannot rely on cloud computing alone. In response to this need …

Network pruning has attracted increasing attention recently for its capability of transferring
large-scale neural networks (eg, CNNs) into resource-constrained devices. Such a transfer …