Scene understanding plays a crucial role in autonomous driving by utilizing sensory data for
contextual information extraction and decision making. Beyond modeling advances, the …

Piezoelectric and triboelectric nanogenerators are at the forefront of converting ambient
mechanical energy into electricity. These devices have experienced significant …

In recent years, Human Activity Recognition (HAR) has become one of the most important
research topics in the domains of health and human-machine interaction. Many Artificial …

Haze superimposes a veil over remote sensing images, which severely limits the extraction
of valuable military information. To this end, we present a novel trinity model to restore …

The planet Earth is being affected by a series of wildfires, which have been steadily
increasing over the last two decades. Forests have undergone deforestation due to natural …

The integration of artificial intelligence (AI) into human activity recognition (HAR) in smart
surveillance systems has the potential to revolutionize behavior monitoring. These systems …

Haze severely degrades the visibility of scene objects and deteriorates the performance of
autonomous driving, traffic monitoring, and other vision-based intelligent transportation …

Dehazing based on deep learning neural networks (CNNs) has achieved remarkable
results. However, the most existing dehazing CNNs perform well only on synthetic images …

The existing remote sensing (RS) image dehazing methods based on deep learning have
sought help from the convolutional frameworks. Nevertheless, the inherent limitations of …

Reducing the atmospheric haze and enhancing image clarity is crucial for computer vision
applications. The lack of real-life hazy ground truth images necessitates synthetic datasets …