Network attack behavior detection using deep learning is an important research topic in the field of network security. Currently, there are still many challenges in detecting multi-class imbalanced ...

Object detection in remote sensing images has long been studied, but it remains challenging due to the diversity of objects and the complexity of backgrounds. In this letter, we propose an object ...

This study (24) introduces the RBP-CNN model, a convolutional neural network designed for precise brain tumor classification in medical imaging. It incorporates regional binary patterns (RBP) and Gray ...

Real-time object detection, which uses neural networks and deep learning to rapidly identify and tag objects of interest in a video feed, is a handy feature with great hacker potential. Happily, it… ...

We propose a novel design to address the problem of real-time unmanned aerial vehicle (UAV) monitoring and detection using a Zynq UltraScale FPGA-based convolutional neural network (CNN). The biggest ...

Firstly, we utilize a network model architecture combining Gelu activation function and deep neural network; Secondly, the cross-entropy loss function is improved to a weighted cross entropy loss ...