Efficient management and accurate monitoring are crucial for the sustainable development
of the aquaculture industry. Traditionally, monitoring methods have relied on single-modality …

Abstract Machine learning methods in healthcare have traditionally focused on using data
from a single modality, limiting their ability to effectively replicate the clinical practice of …

Advances in Artificial Intelligence (AI) and sensors are significantly impacting multiple areas,
including education and workplaces. Following the PRISMA methodology, this review …

Multi-modal medical image fusion enhance the representation, aggregation and
comprehension of functional and structural information, improving accuracy and efficiency …

Detecting Traumatic Brain Injuries (TBI) through imaging remains challenging due to limited
sensitivity in current methods. This study addresses the gap by proposing a novel approach …

In order to improve the detection performance of image fusion in focus areas and realize end-
to-end decision diagram optimization, we design a multi-focus image fusion network based …

In the domain of multi-focus (MF) and multi-model image fusion (MMIF), accurately merging
focused regions from various images remains a challenge. Existing methods often fall short …

Multi-modality medical images are essential in healthcare as they provide valuable insights
for disease diagnosis and treatment. To harness the complementary data provided by …

In remote sensing, the information present in hyperspectral images (HSI) and multispectral
images (MSI) often contrasts with each other. HSI has a higher spectral resolution than …

The COVID-19 pandemic has significantly disrupted traditional medical training, particularly
in critical areas such as the injection process, which require expert supervision. To address …