In this paper, we provide a systematic approach for assessing and comparing the
computational complexity of neural network layers in digital signal processing. We provide …

Industrial products typically lack defects in smart manufacturing systems, which leads to an
extremely imbalanced task of recognizing surface defects. With this imbalanced sample …

Anemia is one of the public health issues that affect children and pregnant women globally.
Anemia occurs when the level of red blood cells within the body is reduced. Detecting …

Experimental results based on offline processing reported at optical conferences
increasingly rely on neural network-based equalizers for accurate data recovery. However …

Background Anaemia is a global public health challenge that affects children and pregnant
women. Anaemia develops when the body's supply of red blood cells declines or when the …

Medical image segmentation is crucial for finding significant areas or characteristics within
images, exclusively in the field of medical identification. Its importance has grown in recent …

Multi-modal foundation models and generative AI have demonstrated promising capabilities
in applications across various domains. Recently, Vision-language-action (VLA) models …

The scarcity of medical imaging datasets and privacy concerns pose significant challenges
in artificial intelligence-based disease prediction. This poses major concerns to patient …

The exponential growth of deep learning networks has enabled us to handle difficult tasks,
even in the complex field of medicine. Nevertheless, for these models to be extremely …

Background: Intracranial neoplasm, often referred to as a brain tumor, is an abnormal growth
or mass of tissues in the brain. The complexity of the brain and the associated diagnostic …