Mathematical biosciences and engineering : MBE
39949163
Epileptic seizures, a prevalent neurological condition, necessitate precise and prompt identification for optimal care. Nevertheless, the intricate characteristics of electroencephalography (EEG) signals, noise, and the want for real-time analysis re...
Automatically generating image captions poses one of the most challenging applications within artificial intelligence due to its integration of computer vision and natural language processing algorithms. This task becomes notably more formidable when...
Human Activity Recognition plays a vital role in various fields, such as healthcare and smart environments. Traditional HAR methods rely on sensor or video data, but sensor-based systems have gained popularity due to their non-intrusive nature. Curre...
Neural networks : the official journal of the International Neural Network Society
39884176
Under the advancement of artificial intelligence, Unmanned Aerial Vehicles (UAVs) exhibit efficient flexibility in military reconnaissance, traffic monitoring, and crop analysis. However, the UAV detection faces unique challenges due to the UAV's sma...
Neural networks : the official journal of the International Neural Network Society
39879865
Shadow removal remains a challenging visual task aimed at restoring the original brightness of shadow regions in images. Many existing methods overlook the implicit clues within non-shadow regions, leading to inconsistencies in the color, texture, an...
Neural networks : the official journal of the International Neural Network Society
39951863
Recent advances in the design of convolutional neural networks have shown that performance can be enhanced by improving the ability to represent multi-scale features. However, most existing methods either focus on designing more sophisticated attenti...
The objects we perceive guide our eye movements when observing real-world dynamic scenes. Yet, gaze shifts and selective attention are critical for perceiving details and refining object boundaries. Object segmentation and gaze behavior are, however,...
Accurate recognition and classification of motor imagery electroencephalogram (MI-EEG) signals are crucial for the successful implementation of brain-computer interfaces (BCI). However, inherent characteristics in original MI-EEG signals, such as non...
Denoising artifacts, such as noise from muscle or cardiac activity, is a crucial and ubiquitous concern in neurophysiological signal processing, particularly for enhancing the signal-to-noise ratio in electroencephalograph (EEG) analysis. Novel metho...
Research on emotion recognition is an interesting area because of its wide-ranging applications in education, marketing, and medical fields. This study proposes a multi-branch convolutional neural network model based on cross-attention mechanism (MCN...