Vision-based techniques for intelligent vehicles in heterogeneous road environments are
gaining significant attention from researchers and industrialists. Unfortunately, the …

Accurate and reliable lane detection is vital for the safe performance of lane‐keeping
assistance and lane departure warning systems. However, under certain challenging …

Edge devices are seeing tremendous growth in sensing and computational capabilities.
Running state-of-the-art deep neural network (NN) based data processing on multi-core …

The prediction of time series data applied to the energy sector (prediction of renewable
energy production, forecasting prosumers' consumption/generation, forecast of country-level …

Transforming the manufacturing environment from manually operated production units to
unsupervised robotic machining centres requires a presence of reliable in-process …

This paper presents a fusion control strategy of adaptive cruise control (ACC) and collision
avoidance (CA), which takes into account a driverʼ s behavioral style. First, a questionnaire …

Research has been continually growing toward the development of image-based structural
health monitoring tools that can leverage deep learning models to automate damage …

Convolutional neural networks (CNNs) were used for the semantic segmentation of angular
monocrystalline WC from NiCrBSi-WC optical microscopy images. This deep learning …

Glioma is a type of fast-growing brain tumor in which the shape, size, and location of the
tumor vary from patient to patient. Manual extraction of a region of interest (tumor) with the …

Abstract Convolutional Neural Networks (CNNs) are gaining significant attention in
applications related to coupled flow and transfer processes in porous media, especially …