Search Results for author: Xinyu Zhou

Found 20 papers, 8 papers with code

A New Learning Paradigm for Stochastic Configuration Network: SCN+

no code implementations11 Mar 2022 Yanshuang Ao, Xinyu Zhou, Wei Dai

This novel algorithm can leverage privileged information into SCN in the training stage, which provides a new method to train SCN.

Incremental Learning

Nanorobot queue: Cooperative treatment of cancer based on team member communication and image processing

no code implementations22 Nov 2021 Xinyu Zhou

Although nanorobots have been used as clinical prescriptions for work such as gastroscopy, and even photoacoustic tomography technology has been proposed to control nanorobots to deliver drugs at designated delivery points in real time, and there are cases of eliminating "superbacteria" in blood through nanorobots, most technologies are immature, either with low efficiency or low accuracy, Either it can not be mass produced, so the most effective way to treat cancer diseases at this stage is through chemotherapy and radiotherapy.

Image Classification

Machine Learning Applications in Forecasting of COVID-19 Based on Patients' Individual Symptoms

no code implementations29 Sep 2021 Zhanyang Sun, Rui Ding, Xinyu Zhou

Predicting the COVID-19 outbreak has been studied by many researchers in recent years.

EventZoom: Learning To Denoise and Super Resolve Neuromorphic Events

no code implementations CVPR 2021 Peiqi Duan, Zihao W. Wang, Xinyu Zhou, Yi Ma, Boxin Shi

EventZoom is trained in a noise-to-noise fashion where the two ends of the network are unfiltered noisy events, enforcing noise-free event restoration.

Denoising Image Reconstruction +1

RPPLNS: Pay-per-last-N-shares with a Randomised Twist

no code implementations15 Feb 2021 Jonathan Katz, Philip Lazos, Francisco J. Marmolejo-Cossío, Xinyu Zhou

"Pay-per-last-$N$-shares" (PPLNS) is one of the most common payout strategies used by mining pools in Proof-of-Work (PoW) cryptocurrencies.

Fairness Computer Science and Game Theory Cryptography and Security

A Review of Automated Diagnosis of COVID-19 Based on Scanning Images

no code implementations9 Jun 2020 Delong Chen, Shunhui Ji, Fan Liu, Zewen Li, Xinyu Zhou

The pandemic of COVID-19 has caused millions of infections, which has led to a great loss all over the world, socially and economically.

14 Computed Tomography (CT) +2

Component-wise Adaptive Trimming For Robust Mixture Regression

no code implementations23 May 2020 Wennan Chang, Xinyu Zhou, Yong Zang, Chi Zhang, Sha Cao

Existing robust mixture regression methods suffer from outliers as they either conduct parameter estimation in the presence of outliers, or rely on prior knowledge of the level of outlier contamination.

Outlier Detection

DPGN: Distribution Propagation Graph Network for Few-shot Learning

1 code implementation CVPR 2020 Ling Yang, Liangliang Li, Zilun Zhang, Xinyu Zhou, Erjin Zhou, Yu Liu

To combine the distribution-level relations and instance-level relations for all examples, we construct a dual complete graph network which consists of a point graph and a distribution graph with each node standing for an example.

Few-Shot Learning

Learning Delicate Local Representations for Multi-Person Pose Estimation

3 code implementations ECCV 2020 Yuanhao Cai, Zhicheng Wang, Zhengxiong Luo, Binyi Yin, Angang Du, Haoqian Wang, Xiangyu Zhang, Xinyu Zhou, Erjin Zhou, Jian Sun

To tackle this problem, we propose an efficient attention mechanism - Pose Refine Machine (PRM) to make a trade-off between local and global representations in output features and further refine the keypoint locations.

Keypoint Detection Multi-Person Pose Estimation

Learning to Run with Actor-Critic Ensemble

1 code implementation25 Dec 2017 Zhewei Huang, Shuchang Zhou, BoEr Zhuang, Xinyu Zhou

We introduce an Actor-Critic Ensemble(ACE) method for improving the performance of Deep Deterministic Policy Gradient(DDPG) algorithm.

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

22 code implementations CVPR 2018 Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, Jian Sun

We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e. g., 10-150 MFLOPs).

Classification General Classification +3

Training Bit Fully Convolutional Network for Fast Semantic Segmentation

no code implementations1 Dec 2016 He Wen, Shuchang Zhou, Zhe Liang, Yuxiang Zhang, Dieqiao Feng, Xinyu Zhou, Cong Yao

Fully convolutional neural networks give accurate, per-pixel prediction for input images and have applications like semantic segmentation.

Semantic Segmentation

Effective Quantization Methods for Recurrent Neural Networks

2 code implementations30 Nov 2016 Qinyao He, He Wen, Shuchang Zhou, Yuxin Wu, Cong Yao, Xinyu Zhou, Yuheng Zou

In addition, we propose balanced quantization methods for weights to further reduce performance degradation.


Scene Text Detection via Holistic, Multi-Channel Prediction

no code implementations29 Jun 2016 Cong Yao, Xiang Bai, Nong Sang, Xinyu Zhou, Shuchang Zhou, Zhimin Cao

Recently, scene text detection has become an active research topic in computer vision and document analysis, because of its great importance and significant challenge.

Scene Text Detection Semantic Segmentation

DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

12 code implementations20 Jun 2016 Shuchang Zhou, Yuxin Wu, Zekun Ni, Xinyu Zhou, He Wen, Yuheng Zou

We propose DoReFa-Net, a method to train convolutional neural networks that have low bitwidth weights and activations using low bitwidth parameter gradients.


Exploiting Local Structures with the Kronecker Layer in Convolutional Networks

no code implementations31 Dec 2015 Shuchang Zhou, Jia-Nan Wu, Yuxin Wu, Xinyu Zhou

In this paper, we propose and study a technique to reduce the number of parameters and computation time in convolutional neural networks.

Scene Text Recognition

Incidental Scene Text Understanding: Recent Progresses on ICDAR 2015 Robust Reading Competition Challenge 4

no code implementations30 Nov 2015 Cong Yao, Jia-Nan Wu, Xinyu Zhou, Chi Zhang, Shuchang Zhou, Zhimin Cao, Qi Yin

Different from focused texts present in natural images, which are captured with user's intention and intervention, incidental texts usually exhibit much more diversity, variability and complexity, thus posing significant difficulties and challenges for scene text detection and recognition algorithms.

Scene Text Detection

ICDAR 2015 Text Reading in the Wild Competition

no code implementations10 Jun 2015 Xinyu Zhou, Shuchang Zhou, Cong Yao, Zhimin Cao, Qi Yin

Recently, text detection and recognition in natural scenes are becoming increasing popular in the computer vision community as well as the document analysis community.

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