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20202024
most citedBrain Tumor Anomaly Detection via Latent Regularized Adversarial Network

9 citations · 21 across the 7 of their papers we have counts for

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5 papers · 1 filter

eess.IV2020★ 9 cited

Brain Tumor Anomaly Detection via Latent Regularized Adversarial Network

Nan Wang, Chengwei Chen, Yuan Xie +1

With the development of medical imaging technology, medical images have become an important basis for doctors to diagnose patients. The brain structure in the collected data is com…

cs.CV2020★ 1 cited

Spoof Face Detection Via Semi-Supervised Adversarial Training

Chengwei Chen, Wang Yuan, Xuequan Lu +1

Face spoofing causes severe security threats in face recognition systems. Previous anti-spoofing works focused on supervised techniques, typically with either binary or auxiliary s…

eess.AS2020★ 2 cited

Acoustic anomaly detection via latent regularized gaussian mixture generative adversarial networks

Chengwei Chen, Pan Chen, Lingyu Yang +4

Acoustic anomaly detection aims at distinguishing abnormal acoustic signals from the normal ones. It suffers from the class imbalance issue and the lacking in the abnormal instance…

cs.CV2020★ 7 cited

Novelty Detection via Non-Adversarial Generative Network

Chengwei Chen, Wang Yuan, Yuan Xie +4

One-class novelty detection is the process of determining if a query example differs from the training examples (the target class). Most of previous strategies attempt to learn the…

cs.CV2020★ 1 cited

Anomaly Detection by One Class Latent Regularized Networks

Chengwei Chen, Pan Chen, Haichuan Song +4

Anomaly detection is a fundamental problem in computer vision area with many real-world applications. Given a wide range of images belonging to the normal class, emerging from some…