Search Results for author: Zhiyong Zhang

Found 14 papers, 0 papers with code

An atrium segmentation network with location guidance and siamese adjustment

no code implementations11 Jan 2023 Yuhan Xie, Zhiyong Zhang, Shaolong Chen, Changzhen Qiu

The segmentation of atrial scan images is of great significance for the three-dimensional reconstruction of the atrium and the surgical positioning.


Spatiotemporal implicit neural representation for unsupervised dynamic MRI reconstruction

no code implementations31 Dec 2022 Jie Feng, Ruimin Feng, Qing Wu, Zhiyong Zhang, Yuyao Zhang, Hongjiang Wei

The high-quality and inner continuity of the images provided by INR has great potential to further improve the spatiotemporal resolution of dynamic MRI, without the need of any training data.

MRI Reconstruction

Face Forgery Detection Based on Facial Region Displacement Trajectory Series

no code implementations7 Dec 2022 Yuyang Sun, Zhiyong Zhang, Isao Echizen, Huy H. Nguyen, Changzhen Qiu, Lu Sun

We introduce a method for detecting manipulated videos that is based on the trajectory of the facial region displacement.

Graph Attention

An Iterative Labeling Method for Annotating Fisheries Imagery

no code implementations27 Apr 2022 Zhiyong Zhang, Pushyami Kaveti, Hanumant Singh, Abigail Powell, Erica Fruh, M. Elizabeth Clarke

In this paper, we present a methodology for fisheries-related data that allows us to converge on a labeled image dataset by iterating over the dataset with multiple training and production loops that can exploit crowdsourcing interfaces.

FakeTransformer: Exposing Face Forgery From Spatial-Temporal Representation Modeled By Facial Pixel Variations

no code implementations15 Nov 2021 Yuyang Sun, Zhiyong Zhang, Changzhen Qiu, Liang Wang, Zekai Wang

With the rapid development of generation model, AI-based face manipulation technology, which called DeepFakes, has become more and more realistic.

DeepFake Detection Face Swapping

Large-scale Transfer Learning for Low-resource Spoken Language Understanding

no code implementations13 Aug 2020 Xueli Jia, Jianzong Wang, Zhiyong Zhang, Ning Cheng, Jing Xiao

However, the increased complexity of a model can also introduce high risk of over-fitting, which is a major challenge in SLU tasks due to the limitation of available data.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Machine learning driven synthesis of few-layered WTe2

no code implementations10 Oct 2019 Manzhang Xu, Bijun Tang, Yuhao Lu, Chao Zhu, Lu Zheng, Jingyu Zhang, Nannan Han, Yuxi Guo, Jun Di, Pin Song, Yongmin He, Lixing Kang, Zhiyong Zhang, Wu Zhao, Cuntai Guan, Xuewen Wang, Zheng Liu

Reducing the lateral scale of two-dimensional (2D) materials to one-dimensional (1D) has attracted substantial research interest not only to achieve competitive electronic device applications but also for the exploration of fundamental physical properties.

BIG-bench Machine Learning

Improved Deep Speaker Feature Learning for Text-Dependent Speaker Recognition

no code implementations28 Jun 2015 Lantian Li, Yiye Lin, Zhiyong Zhang, Dong Wang

A deep learning approach has been proposed recently to derive speaker identifies (d-vector) by a deep neural network (DNN).

Dynamic Time Warping Speaker Recognition

Recognize Foreign Low-Frequency Words with Similar Pairs

no code implementations16 Jun 2015 Xi Ma, Xiaoxi Wang, Dong Wang, Zhiyong Zhang

We also employ this approach to deal with out-of-language words in the task of multi-lingual speech recognition.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Knowledge Transfer Pre-training

no code implementations7 Jun 2015 Zhiyuan Tang, Dong Wang, Yiqiao Pan, Zhiyong Zhang

Compared to the conventional layer-wise methods, this new method does not care about the model structure, so can be used to pre-train very complex models.

speech-recognition Speech Recognition +1

Deep Speaker Vectors for Semi Text-independent Speaker Verification

no code implementations24 May 2015 Lantian Li, Dong Wang, Zhiyong Zhang, Thomas Fang Zheng

Recent research shows that deep neural networks (DNNs) can be used to extract deep speaker vectors (d-vectors) that preserve speaker characteristics and can be used in speaker verification.

Speaker Recognition Text-Dependent Speaker Verification +2

Recurrent Neural Network Training with Dark Knowledge Transfer

no code implementations18 May 2015 Zhiyuan Tang, Dong Wang, Zhiyong Zhang

Recent research found that a well-trained model can be used as a teacher to train other child models, by using the predictions generated by the teacher model as supervision.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

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