Abstract Machine vision was utilized in this study to accurately classify the low concentration
slurry. Orthogonal experiment L9 (34) indicated that the optimal coal slurry collection images …

The diagnosis is influenced by the classification of brain MRIs. Classifying and analyzing
structures within images can be significantly enhanced by employing the Swin Transformer …

Breast cancer remains a significant global health concern, necessitating effective early
detection and prevention strategies. Despite the effectiveness of mammography in early …

In recent years, deep learning's use in medical imaging has grown exponentially. However,
one of the biggest problems with training deep learning models is the unavailability of large …

AI algorithms can analyze medical images, such as X-rays, MRIs, and CT scans, assisting
doctors in detecting diseases and making more accurate diagnoses. However, large …

Brains are complex. This organ stores our knowledge, interprets our senses, moves our
bodies, and governs our thoughts, emotions, memories, vision, touch, respiration, hunger …

This research aims to develop a brain tumor detection model by utilizing the machine
learning techniques and Convolutional Neural Network (CNN). A significant matter to …

Generative artificial intelligence (AI) has enabled tasks in radiology, including tools for
improving image quality. Recently, new hotspots have emerged, such as intra-or inter-modal …

Medical image augmentation plays a crucial role in enhancing the performance of Artificial
Intelligence (AI) applications in medical sciences. Augmenting medical images is important …

The growth of cells in an abnormal and uncontrolled manner leads to tumors. Tumors can be
either benign or cancerous. The tenth highest trigger of mortality for both women and men is …