CLPSTNet

CLPSTNet: A Progressive Multi-Scale Convolutional Steganography Model Integrating Curriculum Learning Fengchun Liu; Tong Zhang; Chunying Zhang This repository contains the official implementation of the paper "CLPSTNet: A Progressive Multi-Scale Convolutional Steganography Model Integrating...

MSCENet: A Multi-Scale Correlation Enhanced Network for Anomaly Detection

In the field of multivariate time series anomaly detection, against the backdrop of increasing data complexity and complex dependencies across multiple temporal scales, traditional methods often struggle to simultaneously capture temporal dynamic features and intricate inter-series correlations. ...

Enhanced Feature Extraction for IoT Network Intrusion Detection Using GNNs and KAN

Recent advancements in the Internet of Things IoT emphasize the urgent need for advanced network security, as IoT networks feature dynamic topologies, imbalanced traffic, and complex attack patterns. Unlike general IT networks, IoT environments exhibit extreme heterogeneity and sparse topologies...

O2Former:Direction-Aware and Multi-Scale Query Enhancement for SAR Ship Instance Segmentation

Instance segmentation of ships in synthetic aperture radar SAR imagery is critical for applications such as maritime monitoring, environmental analysis, and national security. SAR ship images present challenges including scale variation, object density, and fuzzy target boundary, which are often...

CLPSTNet: a Progressive Multi-Scale Convolutional Steganography Model Integrating Curriculum Learning

In recent years, a large number of works have introduced Convolutional Neural Networks CNNs into image steganography, which transform traditional steganography methods such as hand-crafted features and prior knowledge design into steganography methods that neural networks autonomically learn...