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盘州地区峨眉山玄武岩组煤夹层储层特征初探

煤炭技术 2025年第1期44卷 111-115页

作者：唐代学王艇冯运富田永红贵州省地质矿产勘查开发局117地质大队贵阳550018

通过松河井田煤层气探井及相关资料,论证了该区峨眉山玄武岩组煤系夹层32^(#)煤层发育情况、煤层特征等;对比分析了玄武岩组煤系夹层32^(#)煤与龙潭组3^(#)煤在煤体结构、煤层厚度、渗透率、含气性等煤储层特征,认为玄武岩组32^(#)煤层... 详细信息

通过松河井田煤层气探井及相关资料,论证了该区峨眉山玄武岩组煤系夹层32^(#)煤层发育情况、煤层特征等;对比分析了玄武岩组煤系夹层32^(#)煤与龙潭组3^(#)煤在煤体结构、煤层厚度、渗透率、含气性等煤储层特征,认为玄武岩组32^(#)煤层气抽采前景较好,可作为龙潭组煤层气地面抽采的有效补充。

关键词：峨眉山玄武岩组煤系夹层储存特征松河井田

Cluster structure prediction via CALYPSO method

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Chinese Physics B 2019年第10期28卷 1-9页

作者： yonghong tian Weiguo Sun Bole Chen Yuanyuan Jin Cheng Lu Department of Physics and Optoelectronic Engineering Yangtze UniversityJingzhou 434023China Centre for Science at Extreme Conditions and SUPA School of Physics and AstronomyThe University of EdinburghEdinburgh EH9 3FDUnited Kingdom School of Mathematics and Physics China University of Geosciences(Wuhan)Wuhan 430074China Department of Physics and Astronomy University of NevadaLas VegasNevada 89154USA

Cluster science as a bridge linking atomic molecular physics and condensed matter inspired the nanomaterials development in the past decades, ranging from the single-atom catalysis to ligand-protected noble metal clusters. The corresponding studies not only have been restricted to the search for the geometrical structures of clusters, but also have promoted the development of cluster-assembled materials as the building blocks. The CALYPSO cluster prediction method combined with other computational techniques have significantly stimulated the development of the cluster-based nanomaterials. In this review, we will summarize some good cases of cluster structure by CALYPSO method, which have also been successfully identified by the photoelectron spectra experiments. Beginning with the alkali-metal clusters, which serve as benchmarks, a series of studies are performed on the size-dependent elemental clusters which possess relatively high stability and interesting chemical physical properties. Special attentions are paid to the boron-based clusters because of their promising applications. The NbSi12 and BeB16 clusters, for example, are two classic representatives of the silicon-and boron-based clusters, which can be viewed as building blocks of nanotubes and borophene. This review offers a detailed description of the structural evolutions and electronic properties of medium-sized pure and doped clusters, which will advance fundamental knowledge of cluster-based nanomaterials and provide valuable information for further theoretical and experimental studies.

关键词： CALYPSO method cluster structure prediction boron cluster silicon cluster

Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey

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Machine Intelligence Research 2023年第4期20卷 447-482页

作者： Xiao Wang Guangyao Chen Guangwu Qian Pengcheng Gao Xiao-Yong Wei Yaowei Wang yonghong tian Wen Gao Peng Cheng Laboratory Shenzhen518055China School of Computer Science and Technology Anhui UniversityHefei230601China School of Computer Science Peking UniversityBeijing100871China College of Computer Science Sichuan UniversityChengdu610065China

With the urgent demand for generalized deep models,many pre-trained big models are proposed,such as bidirectional encoder representations(BERT),vision transformer(ViT),generative pre-trained transformers(GPT),*** by the success of these models in single domains(like computer vision and natural language processing),the multi-modal pre-trained big models have also drawn more and more attention in recent *** this work,we give a comprehensive survey of these models and hope this paper could provide new insights and helps fresh researchers to track the most cutting-edge ***,we firstly introduce the background of multi-modal pre-training by reviewing the conventional deep learning,pre-training works in natural language process,computer vision,and ***,we introduce the task definition,key challenges,and advantages of multi-modal pre-training models(MM-PTMs),and discuss the MM-PTMs with a focus on data,objectives,network architectures,and knowledge enhanced *** that,we introduce the downstream tasks used for the validation of large-scale MM-PTMs,including generative,classification,and regression *** also give visualization and analysis of the model parameters and results on representative downstream ***,we point out possible research directions for this topic that may benefit future *** addition,we maintain a continuously updated paper list for large-scale pre-trained multi-modal big models:https://***/wangxiao5791509/MultiModal_BigModels_Survey.

关键词： Multi-modal(MM) pre-trained model(PTM) information fusion representation learning deep learning

Introduction to AVS2 Scene Video Coding Techniques

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ZTE Communications 2016年第1期14卷 50-53页

作者： Jiaying Yan Siwei Dong yonghong tian Tiejun Huang National Engineering Laboratory for Video Technology School of EE & CS Peking University School of Electronic and Computer Engineering Shenzhen Graduate School Peking University Cooperative Medianet Innovation Center

The second generation Audio Video Coding Standard (AVS2) is the most recent video coding standard. By introducing several new coding techniques, AVS2 can provide more efficient compression for scene videos such as surveillance videos, conference videos, etc. Due to the limited scenes, scene videos have great redundancy especially in background region. The new scene video coding techniques applied in AVS2 mainly focus on reducing redundancy in order to achieve higher compression. This paper introduces several important AVS2 scene video coding techniques. Experimental results show that with scene video coding tools, AVS2 can save nearly 40%BD?rate (Bj?ntegaard?Delta bit?rate) on scene videos.

关键词： AVS2 scene videos coding background prediction

Toward the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes

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Engineering 2020年第4期6卷 449-461页

作者： Zhaofei Yu Jian K.Liu Shanshan Jia Yichen Zhang Yajing Zheng yonghong tian Tiejun Huang National Engineering Laboratory for Video Technology School of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China Peng Cheng Laboratory Shenzhen 518055China Center for Systems Neuroscience Department of NeurosciencePsychology and BehaviourUniversity of LeicesterLeicester LE17RHUK

A neuroprosthesis is a type of precision medical device that is intended to manipulate the neuronal signals of the brain in a closed-loop fashion,while simultaneously receiving stimuli from the environment and controlling some part of a human brain or *** visual information can be processed by the brain in millisecond *** retina computes visual scenes and sends its output to the cortex in the form of neuronal spikes for further ***,the neuronal signal of interest for a retinal neuroprosthesis is the neuronal ***-loop computation in a neuroprosthesis includes two stages:encoding a stimulus as a neuronal signal,and decoding it back into a *** this paper,we review some of the recent progress that has been achieved in visual computation models that use spikes to analyze natural scenes that include static images and dynamic *** hypothesize that in order to obtain a better understanding of the computational principles in the retina,a hypercircuit view of the retina is necessary,in which the different functional network motifs that have been revealed in the cortex neuronal network are taken into consideration when interacting with the *** different building blocks of the retina,which include a diversity of cell types and synaptic connections-both chemical synapses and electrical synapses(gap junctions)-make the retina an ideal neuronal network for adapting the computational techniques that have been developed in artificial intelligence to model the encoding and decoding of visual *** overall systems approach to visual computation with neuronal spikes is necessary in order to advance the next generation of retinal neuroprosthesis as an artificial visual system.

关键词： Visual coding Retina Neuroprosthesis Brain-machine interface Artificial intelligence Deep learning Spiking neural network Probabilistic graphical model

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仿视网膜传感器视觉重建算法研究综述

中国科学：信息科学 2023年第3期53卷 417-436页

作者：朱林田永鸿北京大学计算机学院北京100871 鹏城实验室深圳518000

视网膜启发的传感器(又称仿视网膜传感器)是近年来新兴的视觉传感器,其通过对场景光强信息进行连续采样,输出高时间分辨率的异步脉冲信号.本文将围绕基于仿视网膜传感器的采样原理进行总结,包括空间对比度传感器、时间对比度传感器、时... 详细信息

视网膜启发的传感器(又称仿视网膜传感器)是近年来新兴的视觉传感器,其通过对场景光强信息进行连续采样,输出高时间分辨率的异步脉冲信号.本文将围绕基于仿视网膜传感器的采样原理进行总结,包括空间对比度传感器、时间对比度传感器、时域积分传感器,以及其他具有附加采样电路的仿视网膜传感器.相对于传统相机,仿视网膜传感器具有高动态范围、高时域分辨率的特征.但是,以1和0(或-1)形式存储的脉冲信号难以与传统视觉信号兼容.如果把仿视网膜采样看作场景光强的紧凑编码过程,那么视觉信息重建即为视觉信息的解码过程.因此,视觉信息重建可以成为一个连接仿视网膜传感器与传统视觉的桥梁.近年来,出现了一些利用异步脉冲信号进行图像重构的算法,通过对脉冲信号进行一系列处理,可以重构出高时域分辨率的图片.本文综述了仿视网膜传感器的采样原理及分类,总结了目前基于事件相机和脉冲相机的视觉信息重建方法.同时,探讨和展望了仿视网膜采样和视觉信息重建的机遇和挑战,以及可能的发展方向.

关键词：仿视网膜传感器仿视网膜采样机制神经形态相机图像重构光流估计深度估计

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引入混沌差分控制理论的温度控制器设计

科技通报 2014年第6期30卷 225-227页

作者：田永红四川理工学院计算机学院四川自贡643000

针对工业控制中的温度快速变换过程中的干扰问题,引入一种混沌差分控制温度控制的思想,分析炉内温度场中火焰时间序列中的带有非线性混沌特征,以ARM9控制芯片为基础,利用火焰时间序列混沌变量的非线性随机性、遍历性进行温度优化控制,... 详细信息

针对工业控制中的温度快速变换过程中的干扰问题,引入一种混沌差分控制温度控制的思想,分析炉内温度场中火焰时间序列中的带有非线性混沌特征,以ARM9控制芯片为基础,利用火焰时间序列混沌变量的非线性随机性、遍历性进行温度优化控制,把混沌理论引入到温度优化控制当中,消除干扰影响。实验结果表明,该方法提高了控制器的静态温度和动态温度控制精确,波动系数小,状态稳定。

关键词：温度控制 AMR9 混沌理论

Perspective:Societally connected multimedia across cultures

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Journal of Zhejiang University-Science C(Computers and Electronics) 2012年第12期13卷 875-880页

作者： Zhongfei ZHANG Zhengyou ZHANG Ramesh JAIN Yueting ZHUANG Noshir CONTRACTOR Alexander G. HAUPTMANN Alejandro (Alex) JAIMES Wanqing LI Alexander C. LOUI Tao MEI Nicu SEBE yonghong tian Vincent S. TSENG Qing WANG Changsheng XU Huimin YU Shiwen YU Department of lnformation Science & Electronic Engineering Zhejiang University Hangzhou 310027 China Microsoft Research Redmond WA USA Department of Computer Science University of California IrvineCA USA College of Computer Science and Technology Zhejiang UniversityHangzhou 310027 China School of Communication Northwestern University Evanston 1LUSA Informedia Group CMU Pittsburgh PA Yahoo.t Research Spain School of Computer Science and Software Engineering Universityof Wollongong NSW Australia Kodak Research Labs USA Microsoft Research Asia China Department of Information Engineering and Computer Science University of Trento Italy Institute of Computational Linguistics Peking University Beijing100871 China Institute of Computer Science and Information National ChengKung University Taiwan 701 Tainan School of Computer Science Northwestern Polytechnical UniversityXi'an 710129 China Institute of Automation Chinese Academy of Sciences Beijing100080 China

The advance of the Internet in the past decade has radically changed the way people communicate and col- laborate with each other. Physical distance is no more a barrier in online social networks, but cultural differences （at the individual, community, as well as societal levels） still govern human-human interactions and must be con- sidered and leveraged in the online world. The rapid deployment of high-speed lnternet allows humans to interact using a rich set of multimedia data such as texts, pictures, and videos. This position paper proposes to define a new research area called ＇connected multimedia＇, which is the study of a collection of research issues of the super-area social media that receive little attention in the literature. By connected multimedia, we mean the study of the social and technical interactions among users, multimedia data, and devices across cultures and explicitly exploiting the cultural differences. We justify why it is necessary to bring attention to this new research area and what benefits of this new research area may bring to the broader scientific research community and the humanity.

关键词： Connected multimedia Social media Social-cultural constraint

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紧致化神经网络的鲁棒性分析

中国科学：技术科学 2022年第5期52卷 689-703页

作者：陈光耀彭佩玺田永鸿北京大学计算机科学技术系北京100871 鹏城实验室深圳518055

深度神经网络(deep neural network,DNN)目前已经在很多视觉识别任务中达到了超越人类性能的表现.然而,将深度神经网络部署到真实场景的终端设备面临着两个挑战:首先,目前的深度神经网络模型非常耗费计算资源和内存,很难直接应用在资源... 详细信息

深度神经网络(deep neural network,DNN)目前已经在很多视觉识别任务中达到了超越人类性能的表现.然而,将深度神经网络部署到真实场景的终端设备面临着两个挑战:首先,目前的深度神经网络模型非常耗费计算资源和内存,很难直接应用在资源受限的终端设备上;其次,真实场景的数据往往受到各种各样噪声的影响,因此部署在真实场景的模型应该拥有良好的鲁棒性(robustness).近年来出现了很多对深度神经网络进行压缩和加速的方法以适应真实场景的资源受限终端,而对这些压缩模型的鲁棒性分析也得到了越来越多的关注.本文首次对神经网络剪枝、量化及知识蒸馏等常用的压缩算法进行对抗鲁棒性及噪声鲁棒性分析,总结了不同压缩算法对神经网络鲁棒性的影响.并对目前同时解决神经网络鲁棒性及模型大小问题的一些方案进行了整理与分析,展望了该领域未来研究的技术挑战与可能的发展方向.

关键词：神经网络量化与剪枝知识蒸馏鲁棒性分析