中国科学院机构知识库网格系统: 检索

IAN: Instance-Augmented Net for 3D Instance Segmentation 期刊论文 OAI收割
IEEE ROBOTICS AND AUTOMATION LETTERS, 2023, 卷号: 8, 期号: 7, 页码: 4354-4361
作者: Wan, Zihao; Hu, Jianhua; Zhang, Haojian; Wang, Yunkuan

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收藏 | 浏览/下载：22/0 | 提交时间：2023/11/17

Three-dimensional displays Feature extraction Point cloud compression Solid modeling Semantics Noise measurement Aggregates Deep learning for visual perception RGB-D perception data sets for robotic vision

Not All Samples are Trustworthy: Towards Deep Robust SVP Prediction 期刊论文 OAI收割
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2022, 卷号: 44, 期号: 6, 页码: 3154-3169
作者: Xu, Qianqian; Yang, Zhiyong; Jiang, Yangbangyan; Cao, Xiaochun; Yao, Yuan

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收藏 | 浏览/下载：37/0 | 提交时间：2022/12/07

Noise measurement Annotations Task analysis Predictive models Robustness Visualization Training Subjective visual property (SVP) robustness outlier detection probabilistic model

Visual Dysfunction in Chinese Children With Developmental Dyslexia: Magnocellular-Dorsal Pathway Deficit or Noise Exclusion Deficit? 期刊论文 OAI收割
FRONTIERS IN PSYCHOLOGY, 2020, 卷号: 11, 页码: 11
作者: Ji, Yuzhu; Bi, Hong-Yan

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收藏 | 浏览/下载：38/0 | 提交时间：2020/08/03

developmental dyslexia magnocellular theory noise exclusion Chinese children visual dysfunction

Performance Evaluation of Visual Noise Imposed Stochastic Resonance Effect on Brain-Computer Interface Application: A Comparison Between Motion-Reversing Simple Ring and Complex Checkerboard Patterns 期刊论文 OAI收割
FRONTIERS IN NEUROSCIENCE, 2019, 卷号: 13, 页码: 1-13
作者: Xie J(谢俊); Du, Guangjing; Xu GH(徐光华); Zhao XG(赵新刚); Fang, Peng

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收藏 | 浏览/下载：59/0 | 提交时间：2019/12/14

brain-computer interface (BCI) visual noise stochastic resonance (SR) motion-reversing stimulation checkerboard single ring

Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface 期刊论文 OAI收割
FRONTIERS IN NEUROROBOTICS, 2018, 卷号: 12, 页码: 10
作者: Xie, Jun; Xu, Guanghua; Zhao, Xingang; Li, Min; Wang, Jing

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收藏 | 浏览/下载：17/0 | 提交时间：2021/02/02

brain-computer interface (BCI) motion-reversal stimulation plasticity visual evoked potential (VEP) visual noise

Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface 期刊论文 OAI收割
FRONTIERS IN NEUROROBOTICS, 2018, 卷号: 12, 页码: 1-10
作者: Han, Chengcheng; Han, Xingliang; Xie J(谢俊); Xu GH(徐光华); Zhao XG(赵新刚)

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收藏 | 浏览/下载：37/0 | 提交时间：2018/12/16

Brain-computer Interface (Bci) Motion-reversal Stimulation Plasticity Visual Evoked Potential (Vep) Visual Noise

Centroid localization algorithm based on bicubic interpolation gray square weighted (EI CONFERENCE) 会议论文 OAI收割
2012 3rd International Conference on Advances in Materials and Manufacturing Processes, ICAMMP 2012, December 22, 2012 - December 23, 2012, Beihai, China
作者: Zhou J.

收藏 | 浏览/下载：152/0 | 提交时间：2013/03/25

The 3D coordinates of measured point is embodied in 2D image coordinate of the optical characteristic point via the visual measurement system. Based on the gray square weighted centroid localization algorithm the paper presents bicubic interpolation gray square weighted centroid localization algorithm increases the number of effective pixels around the optical characteristic point imaging center and reduces noise error via the gray square weighted improves the imaging center location accuracy of optical characteristic point realizes the accurate location of the optical characteristic points. Results indicate application of the proposed algorithm to location the standard tolerance along the direction of x is 0.0022 Pixel the standard tolerance along the direction of y is 0.0023 Pixel compared with the others the standard tolerance is minimum and discrete to a lesser degree distancing ideal image point that is the proposed algorithm has higher location accuracy. The maximum tolerance along the direction of x is 0.008 Pixel the one along the direction of y is 0.007 Pixel compared with the other two algorithms the maximum tolerance is minimum.Results indicate that the stability of the proposed algorithm is better. (2013) Trans Tech Publications Switzerland.

Similar spatial patterns of neural coding of category selectivity in FFA and VWFA under different attention conditions 期刊论文 OAI收割
NEUROPSYCHOLOGIA, 2012, 卷号: 50, 期号: 5, 页码: 862-868
作者: Xu, Guifang; Jiang, Yi; Ma, Lifei; Yang, Zhi; Weng, Xuchu

收藏 | 浏览/下载：23/0 | 提交时间：2015/08/31

fMRI Fusiform face area Visual word form area Multi-voxel pattern analysis (MVPA) Contrast-to-noise ratio

The application of adaptive enhancement algorithm based on gray entropy in mammary gland CR image (EI CONFERENCE) 会议论文 OAI收割
2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012, April 21, 2012 - April 23, 2012, Three Gorges, China
Zhang M.-H.; Zhang Y.-Y.

收藏 | 浏览/下载：34/0 | 提交时间：2013/03/25

Mammary gland is composed entirely of soft tissue with approximate density therefore mammary gland CR medicine radiation image presents a low contrast and slight difference changes may be a manifestation of tumor so it is necessary to enhance mammary gland CR image to improve its visual quality in order to meet the demands of doctor's clinical diagnosis. However the general enhancement algorithms over enhance the contrast and noise due to image details lost aiming at the defects a mammary gland CR medicine image adaptive enhancement arithmetic based on image gray entropy is put forward. The arithmetic adapts dizzy image to magnify selected spatial frequency response in order to enhance the edge details of mammary gland CR images. It can adjust weighted factor K according to image gray characteristics namely pixel gray entropy. Experiments results demonstrate that mammary gland CR image enhanced by the algorithm has abundant details and high signal-to-noise ratio moreover CR image enhanced has good visual effect. So the method is effective and fit for enhancing CR medical radiation image edge details. 2012 IEEE.

The research of digltal CR medicine image adapitive enhancement method (EI CONFERENCE) 会议论文 OAI收割
4th International Conference on Mechanical and Electrical Technology, ICMET 2012, July 24, 2012 - July 26, 2012, Kuala Lumpur, Malaysia
Ming-Hui Z.; Yao-Yu Z.

收藏 | 浏览/下载：65/0 | 提交时间：2013/03/25

Digital CR medicine radiation image is in doctor's favor and has became medicine imaging technology new hot spot because of its high gray contrast powerful computer disposal function little radiation dosage non-film diagnosis different area consultation. But degradation of digital X-ray medical image such as low contrast and blurring during radiographic imaging caused by complexity of body tissue and effects of X-ray scattering and electrical noise etc. can worsen the results of analysis and diagnosis. So it is usually needed that CR medicine image is enhanced to improve its vision quality and easy to doctor's more accurate diagnosis. The general enhancement algorithms over enhancing the contrast and lose image details aiming at the defects an enhancement algorithm for CR image is proposed based on the ratio of deviation to mean of domain. The arithmetic enhance CR image edge details by adjusting factor K based on the ratio of deviation to mean of domain of CR image. Experiment results demonstrate that the algorithm enhances CR image detail and CR image enhanced has good visual effect the adaptive enhancement method is fit for CR medicine image. (2012) Trans Tech Publications Switzerland.