Abstract: Early detection of tsunamis is essential for disaster risk reduction and minimizing loss of life. This research introduces an advanced deep learning-based tsunami detection model that ...
Abstract: The rise of mpox as a global health concern highlights the necessity of effective early detection strategies to manage its propagation. Though less fatal than COVID-19, mpox poses some ...
Machine learning models reveal that histone marks are predictive of gene expression across human cell types and highlight important nuances between natural control and the effects of CRISPR-Cas9-based ...
The integration of sleep-based AI into routine health check-ups represents a significant leap forward in personalised ...
Abstract: This article proposes an improved deep reinforcement learning algorithm for complete coverage path planning of mobile robots. The algorithm addresses the issue of agents easily getting ...
Abstract: Early and precise detection of plant diseases is crucial for enhancing crop yield and minimizing agricultural losses. This paper evaluates the performance of deep learning-based ...
Abstract: Power distribution networks (PDNs) require accurate schematic interpretation for efficient operation and maintenance. Manual text detection is labor-intensive and error-prone, necessitating ...
Abstract: Cybersecurity risks have evolved in the linked digital terrain of today into more complex, frequent, and varied forms. Conventional intrusion detection systems sometimes find it difficult to ...
CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
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