We study the effectiveness of Feature Density (FD) using different linguistically-backed
feature preprocessing methods in order to estimate dataset complexity, which in turn is used …

Recent progress in encoder–decoder neural network architecture design has led to
significant performance improvements in a wide range of medical image segmentation …

Data augmentation has emerged as a widely adopted technique for improving the
generalization capabilities of deep neural networks. However, evaluating the effectiveness …

Due to the rapid development of deep learning, object detection models have become the
current tool of choice for on-tree fruit detection in precision agriculture. The pipeline of fruit …

We investigate the advantages of using co-packaged optics for building low-diameter, large-
scale high-performance computing (HPC) and data center networks. The increased escape …

Universal filtered multicarrier (UFMC) has emerged as a potential waveform contender of
orthogonal frequency division multiplexing (OFDM) for the fifth generation (5G) and beyond …

Grinding tools can be used for over 90% of their lifetime, but most practical production tools
are replaced between 50 and 80%. Accurate tool condition monitoring, which can monitor …

Real-world images often encompass embedded texts that adhere to disparate disciplines
like business, education, and amusement, to name a few. Such images are graphically rich …

This study presents an innovative approach for automatic road detection with deep learning,
employing fusion strategies to utilize both lower-resolution satellite imagery and GPS …

Applications using machine learning (ML), such as highly autonomous driving, depend
highly on the performance of the ML model. The data amount and quality used for model …