2 citations · 3 across the 8 of their papers we have counts for
8 papers
Mask-Robust Face Verification for Online Learning via YOLOv5 and Residual Networks
Zhifeng Wang, Minghui Wang, Chunyan Zeng +3
In the contemporary landscape, the fusion of information technology and the rapid advancement of artificial intelligence have ushered school education into a transformative phase c…
Dynamically Weighted Momentum with Adaptive Step Sizes for Efficient Deep Network Training
Zhifeng Wang, Longlong Li, Chunyan Zeng
Within the current sphere of deep learning research, despite the extensive application of optimization algorithms such as Stochastic Gradient Descent (SGD) and Adaptive Moment Esti…
Multi-Scale Deformable Transformers for Student Learning Behavior Detection in Smart Classroom
Zhifeng Wang, Minghui Wang, Chunyan Zeng +1
The integration of Artificial Intelligence into the modern educational system is rapidly evolving, particularly in monitoring student behavior in classrooms, a task traditionally d…
Using Scene and Semantic Features for Multi-modal Emotion Recognition
Zhifeng Wang, Ramesh Sankaranarayana
Automatic emotion recognition is a hot topic with a wide range of applications. Much work has been done in the area of automatic emotion recognition in recent years. The focus has…
DSARSR: Deep Stacked Auto-encoders Enhanced Robust Speaker Recognition
Zhifeng Wang, Chunyan Zeng, Surong Duan +2
Speaker recognition is a biometric modality that utilizes the speaker's speech segments to recognize the identity, determining whether the test speaker belongs to one of the enroll…
Learning Behavior Recognition in Smart Classroom with Multiple Students Based on YOLOv5
Zhifeng Wang, Jialong Yao, Chunyan Zeng +3
Deep learning-based computer vision technology has grown stronger in recent years, and cross-fertilization using computer vision technology has been a popular direction in recent y…
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…
Digital Audio Tampering Detection Based on ENF Spatio-temporal Features Representation Learning
Chunyan Zeng, Shuai Kong, Zhifeng Wang +2
Most digital audio tampering detection methods based on electrical network frequency (ENF) only utilize the static spatial information of ENF, ignoring the variation of ENF in time…