The research advances concerning the typical architectures of convolutional neural
networks (CNNs) as well as their optimizations are analyzed and elaborated in detail in this …

The article focuses on utilizing unmanned aerial vehicles (UAV) to capture and classify
building façades of various forms of cultural sites and structures. We propose a Pareto …

Meander structures are highly relevant in the Internet-of-Things (IoT) communication
systems, their miniaturization remains as one of the key design issues. Meander structures …

The ever increasing computational cost of Deep Neural Networks (DNN) and the demand for
energy efficient hardware for DNN acceleration has made accuracy and hardware cost co …

Automated machine learning has gained a lot of attention recently. Building and selecting
the right machine learning models is often a multi-objective optimization problem. General …

Recent studies on automatic neural architecture search techniques have demonstrated
significant performance, competitive to or even better than hand-crafted neural architectures …

The important, while mostly underestimated, step in the process of short-term load
forecasting–STLF is the selection of similar days. Similar days are identified based on …

Recent studies on automatic neural architectures search have demonstrated significant
performance, competitive to or even better than hand-crafted neural architectures. However …

A graph neural network is a deep learning model for processing graph data. In recent years,
graph neural network architectures have become more and more complex as the research …

Convolutional Neural networks (CNN) have been utilized in a wide variety of areas, with a
high degree of performance. The design of the CNN has been a general problem addressed …