Application of deep ensemble learning for palm disease detection in smart agriculture.

Agriculture has notably become one of the fields experiencing intensive digital transformation. Leveraging state-of-the-art techniques in this domain has provided numerous advantages for agricultural activities. Deep learning (DL) algorithms have proven beneficial in addressing various agricultural challenges.

Enhancing Disease Classification with Deep Learning: a Two-Stage Optimization Approach for Monkeypox and Similar Skin Lesion Diseases.

Monkeypox (MPox) is an infectious disease caused by the monkeypox virus, presenting challenges in accurate identification due to its resemblance to other diseases. This study introduces a deep learning-based method to distinguish visually similar diseases, specifically MPox, chickenpox, and measles, addressing the 2022 global MPox outbreak. A two-stage optimization approach was presented in the study.

Cyber governance studies in ensuring cybersecurity: an overview of cybersecurity governance.

With the exponential increase of digital data in cyber environments, security measures have gained more importance. Cybersecurity threats are revealed by national and international units, and the number of these threats is increasing daily. The elimination of cybersecurity risks is possible with an effective cybersecurity strategy.

Correction to: Classification of Carotid Artery Intima Media Thickness Ultrasound Images with Deep Learning.

The original article unfortunately contained a mistake. Figure 2b was removed in the article.

Classification of Carotid Artery Intima Media Thickness Ultrasound Images with Deep Learning.

Cerebrovascular accident due to carotid artery disease is the most common cause of death in developed countries following heart disease and cancer. For a reliable early detection of atherosclerosis, Intima Media Thickness (IMT) measurement and classification are important. A new method for decision support purpose for the classification of IMT was proposed in this study.