To stop vision loss from glaucoma, early identification and regular screening are crucial. Convolutional neural networks (CNN) have been effectively used in recent years to diagnose glaucoma automatically from color fundus pictures. CNNs can extract distinctive characteristics directly from the fundus pictures, as opposed to the current automatic screening techniques. In this study, a CNN-based […]
Through the use of malware, particularly JavaScript, cybercriminals have turned online applications into one of their main targets for impersonation. Detection of such dangerous code in real-time, therefore, becomes crucial in order to prevent any harmful action. By categorizing the salient characteristics of the malicious code, this study suggests an effective technique for identifying malicious […]
Wildfire detection is a time-critical application since it can be challenging to identify the source of ignition in a short amount of time, which frequently causes the intensity of fire incidents to increase. The development of precise early-warning applications has sparked significant interest in expert systems research due to this issue, and recent advances in […]
The rapid increase in the number of medical image repositories nowadays has led to problems in managing and retrieving medical visual data. This has proved the necessity of Content-Based Image Retrieval (CBIR) with the aim of facilitating the investigation of such medical imagery. One of the most serious challenges that require special attention is the […]
