A neural network-aided detection scheme for index-modulation dcsk system
The accuracy of index-bit detection greatly affects the overall bit-error-rate (BER)
performance of index modulation aided differential chaos shift keying (IM-DCSK). To …
performance of index modulation aided differential chaos shift keying (IM-DCSK). To …
Moana: An online learned adaptive appearance model for robust multiple object tracking in 3d
Multiple object tracking has been a challenging field, mainly due to noisy detection sets an
identity switch caused by occlusion and similar appearance among nearby targets. Previous …
identity switch caused by occlusion and similar appearance among nearby targets. Previous …
Heuristically mining the top-k high-utility itemsets with cross-entropy optimization
W Song, C Zheng, C Huang, L Liu - Applied Intelligence, 2022 - Springer
Mining high-utility itemsets (HUIs) is one of the most important research topics in data mining
because HUIs consider non-binary frequency values of items in transactions and different …
because HUIs consider non-binary frequency values of items in transactions and different …
[HTML][HTML] Two decades of vehicle make and model recognition–survey, challenges and future directions
Vehicle make and model recognition (VMMR) is a crucial task for developing automatic
vehicle recognition (AVR) systems, and has gained significant attention in the fields of …
vehicle recognition (AVR) systems, and has gained significant attention in the fields of …
[HTML][HTML] Towards an effective intrusion detection model using focal loss variational autoencoder for internet of things (IoT)
As the range of security attacks increases across diverse network applications, intrusion
detection systems are of central interest. Such detection systems are more crucial for the …
detection systems are of central interest. Such detection systems are more crucial for the …
Improving data generalization with variational autoencoders for network traffic anomaly detection
Deep generative models have increasingly become popular in different domains such as
image processing, though, they hardly appear in the cybersecurity arena. While the main …
image processing, though, they hardly appear in the cybersecurity arena. While the main …
Fused adaptive receptive field mechanism and dynamic multiscale dilated convolution for side-scan sonar image segmentation
Z Wang, S Zhang, L Gross, C Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Side-scan sonar (SSS) is a vital sensor for marine survey, which is widely used in military
and civilian fields. The accurate segmentation of SSS images is critical in sonar image …
and civilian fields. The accurate segmentation of SSS images is critical in sonar image …
[HTML][HTML] Defense against adversarial patch attacks for aerial image semantic segmentation by robust feature extraction
Z Wang, B Wang, C Zhang, Y Liu - Remote Sensing, 2023 - mdpi.com
Deep learning (DL) models have recently been widely used in UAV aerial image semantic
segmentation tasks and have achieved excellent performance. However, DL models are …
segmentation tasks and have achieved excellent performance. However, DL models are …
Intentional deep overfit learning (IDOL): A novel deep learning strategy for adaptive radiation therapy
Purpose Applications of deep learning (DL) are essential to realizing an effective adaptive
radiotherapy (ART) workflow. Despite the promise demonstrated by DL approaches in …
radiotherapy (ART) workflow. Despite the promise demonstrated by DL approaches in …
An Intelligent Detection Based on Deep Learning for Multilevel Code Shifted Differential Chaos Shift Keying System With M-ary Modulation
Multilevel code shifted-ary differential chaos shift keying (MCS-MDCSK) system provides
higher data rate chaotic information transmission by applying multilevel code shifting aided …
higher data rate chaotic information transmission by applying multilevel code shifting aided …