CNN Model

Convolutional Neural Networks (CNNs) are a fundamental deep learning architecture primarily used for image processing tasks, aiming to efficiently extract and classify features from visual data. Current research focuses on improving CNN efficiency and robustness, exploring variations like hybrid models integrating transformers, lightweight architectures for resource-constrained devices, and techniques to enhance interpretability and mitigate biases. The widespread applicability of CNNs spans diverse fields, from medical image analysis and object detection in autonomous systems to artistic creativity assessment and environmental monitoring, significantly impacting both scientific understanding and practical applications.