most citedAbs-CAM: A Gradient Optimization Interpretable Approach for Explanation of Convolutional Neural Networks

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD2022

End-to-end Recording Device Identification Based on Deep Representation Learning

Chunyan Zeng, Dongliang Zhu, Zhifeng Wang +3

Deep learning techniques have achieved specific results in recording device source identification. The recording device source features include spatial information and certain temp…

cs.CV2022★ 2 cited

JSRNN: Joint Sampling and Reconstruction Neural Networks for High Quality Image Compressed Sensing

Chunyan Zeng, Jiaxiang Ye, Zhifeng Wang +2

Most Deep Learning (DL) based Compressed Sensing (DCS) algorithms adopt a single neural network for signal reconstruction, and fail to jointly consider the influences of the sampli…

cs.SD2022

Audio Tampering Detection Based on Shallow and Deep Feature Representation Learning

Zhifeng Wang, Yao Yang, Chunyan Zeng +3

Digital audio tampering detection can be used to verify the authenticity of digital audio. However, most current methods use standard electronic network frequency (ENF) databases f…

cs.SD2022

Spatio-Temporal Representation Learning Enhanced Source Cell-phone Recognition from Speech Recordings

Chunyan Zeng, Shixiong Feng, Zhifeng Wang +3

The existing source cell-phone recognition method lacks the long-term feature characterization of the source device, resulting in inaccurate representation of the source cell-phone…

cs.CV2022★ 3 cited

Abs-CAM: A Gradient Optimization Interpretable Approach for Explanation of Convolutional Neural Networks

Chunyan Zeng, Kang Yan, Zhifeng Wang +3

The black-box nature of Deep Neural Networks (DNNs) severely hinders its performance improvement and application in specific scenes. In recent years, class activation mapping-based…