IEEE

FocalCA: A Hybrid-Convolutional-Attention Encoder for Intrusion Detection on UNSW-NB15 Achieving High Accuracy Without Data Balancing

Abstract: This study introduces FocalCA, a Hybrid Convolutional-Attention Encoder model for detecting CyberAttacks using the UNSW-NB15 dataset. Despite the inherent imbalance in the binary ...
Scientific Research Publishing

Li, F., Qiao, H. and Zhang, B. (2018) Discriminatively Boosted Image Clustering with Fully Convolutional Auto-encoders. Pattern Recognition, 83, 161-173.

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...
Scientific Research Publishing

Mao, X.J., Shen, C. and Yang, Y.B. (2016) Image Restoration Using Convolutional Auto-Encoders with Symmetric Skip Connections.

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...
IEEE

Optimizing the Hyperparameters of Fully Convolutional Encoder–Decoder Networks for SAR Image Segmentation

Abstract: Fully convolutional encoder-decoder networks have been developed for the segmentation of sensing synthetic aperture radar (SAR) images. A recent one called the multiscaled attention U-net ...