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6th Annual 2018 International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2018

作者： Ma, Chengcheng Tian, Ze Liu, Honghong Nie, Zhao China Aeronautical Computing Research Institute China Aviation Key Laboratory of Science and Technology on Integrated Circuit and Micro-System Design P.O. Box 710068 China Xiangteng Microelectronics Technology Co. LTD P.O. Box 710068 China

As the core of GPU processing, the performance of Unified rendering array is directly affected by the shader driver. On the basis of research the structure of Unified rendering array processing, this paper proposes a runtime Unified rendering array driver optimization method for graphical application, can according to different graphics application scenario runtime to generate optimized Unified rendering array driver, testing on graphics processors FPGA verification environment, driven by the runtime optimization compared with the traditional full function driver, performance increased by 55% - 270%. © Published under licence by IOP Publishing Ltd.

关键词： Array processing

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Spin-induced orbital frustration in a hexagonal optical lattice

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Physical Review Research 2021年第3期3卷 033274-033274页

作者： Yongqiang Li Jianmin Yuan Xiaoji Zhou Xiaopeng Li Department of Physics National University of Defense Technology Changsha 410073 People's Republic of China Department of Physics Graduate School of China Academy of Engineering Physics Beijing 100193 People's Republic of China State Key Laboratory of Advanced Optical Communication System and Network Department of Electronics Peking University Beijing 100871 People's Republic of China State Key Laboratory of Surface Physics Institute of Nanoelectronics and Quantum Computing and Department of Physics Fudan University Shanghai 200438 People's Republic of China Shanghai Qi Zhi Institute AI Tower Xuhui District Shanghai 200232 People's Republic of China

Complex lattices provide a versatile ground for fascinating quantum many-body physics. Here, we propose an exotic mechanics for generating orbital frustration in hexagonal lattices. We study two-component (pseudospin-12) Bose gases in p-orbital bands of two-dimensional hexagonal lattices, and find that the system exhibits previously untouched orbital frustration as a result of the interplay of spin and orbital degrees of freedom, in contrast to normal Ising-type orbital ordering of spinless p-orbital band bosons in two-dimensional hexagonal lattices. Based on the classification by symmetry analysis, we find the interplay of orbital frustration and strong interaction leads to exotic Mott and superfluid phases with spin-orbital intertwined orders, in spite of the complete absence of spin-orbital interaction in the Hamiltonian. Our study implies many-body correlations in a multiorbital setting could induce rich spin-orbital intertwined physics in complex lattice structures.

关键词： Bose-Einstein condensates Cold gases in optical lattices Exotic phases of matter Quantum phase transitions Dynamical mean field theory

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Non-structured Pruning for Deep-learning based Steganalytic Frameworks

Non-structured Pruning for Deep-learning based Steganalytic ...

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Qiushi Li Zilong Shao Shunquan Tan Jishen Zeng Bin Li Shenzhen Key Laboratory of Media Security Guangdong Key Laboratory of Intelligent Information Processing National Engineering Laboratory for Big Data System Computing Technology Shenzhen China

ISBN: (数字)9781728132488

ISBN: (纸本)9781728132495

Image steganalysis aims to discriminate innocent cover images and those suspected stego images embedded with secret message. Recently, increasing advanced deep neural networks have been proposed and used in image steganalysis. Though those deep learning models can gain superior performance, they also result in redundancy of computational resource and memory storage. In this paper, we apply a non-structured pruning method to prune XuNet2 and SRNet - the two state-of-the-art deep-learning framework in the field of JPEG image steganalysis. We obtain the priorities of the connections among neurons according to a certain criterion, then keep those significant weights and prune those nonsignificant ones in the meantime. We have conducted extensive experiments on BOSSBase and BOWS image dataset. The experimental results demonstrate that our proposed non-structured pruning method can significantly reduce the cost of computation and storage required by the original deep-learning frameworks without affecting their detection accuracy.

关键词： Transform coding Training Convolution Computer architecture Computational modeling Brain modeling Testing

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DPNet: Dynamic Pooling Network for Accurate and Efficient Size-Aware Tiny Object Detection

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IEEE Internet of Things Journal 2025年

作者： Gong, Luqi Chen, Haotian Chen, Yikun Yao, Tianliang Li, Chao Zhao, Shuai Han, Guangjie Beijing University of Posts and Telecommunications School of Computer Science Beijing China Zhejiang Lab Research Center for Space Computing System Hangzhou China Southwest Jiaotong University SWJTU-LEEDS Joint School Chengdu China LTD Guangdong Zhiyun City construction Technology Co Zhuhai China Tongji University College of Electronic and Information Engineering Department of Control Science and Engineering Shanghai China Hohai University Key Laboratory of Maritime Intelligent Network Information Technology Ministry of Education China

In unmanned aerial systems, especially in complex environments, accurately detecting tiny objects is crucial. Resizing images is a common strategy to improve detection accuracy, particularly for small objects. However, simply enlarging images significantly increases computational costs and the number of negative samples, severely degrading detection performance and limiting its applicability. This paper proposes a Dynamic Pooling Network (DPNet) for tiny object detection to mitigate these issues. DPNet employs a flexible down-sampling strategy by introducing a factor (df) to relax the fixed down-sampling process of the feature map to an adjustable one. Furthermore, we design a lightweight predictor to predict df for each input image, which will be used to decrease the resolution of feature map in backbone. Thus, we achieve input-aware down-sampling. We design an Adaptive Normalization Module (ANM) to make a unified detector well compatible with different dfs. At the same time, we also design a guidance loss to supervise the predictor’s training. DPNet realizes the dynamic allocation of computing resources to trade off detection accuracy and efficiency through this. Experiments on the TinyCOCO and TinyPerson datasets show that our DPNet can save over 35% and 25% GFLOPs, respectively, while maintaining comparable detection *** code will be made publicly available. © 2014 IEEE.

关键词： Object detection

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Hybrid followee recommendation in microblogging systems

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Science China(Information Sciences) 2017年第1期60卷 21-34页

作者： Hanhua CHEN Hai JIN Xiaolong CUI Services Computing Technology and System Laboratory Big Data Technology and System LaboratoryCluster and Grid Computing Laboratory School of Computer Science and TechnologyHuazhong University of Science and Technology

Followee recommendation plays an important role in information sharing over microblogging platforms. Existing followee recommendation schemes adopt either content relevance or social information for followee ranking, suffering poor performance. Based on the observation that microblogging systems have dual roles of social network and news media platform, we propose a novel followee recommendation scheme that takes into account the information sources of both tweet contents and the social structures. We set up a linear weighted model to combine the two factors and further design a simulated annealing algorithm to automatically assign the weights of both factors in order to achieve an optimized combination of them. We conduct comprehensive experiments on real-world datasets collected from Sina Weibo, the largest microblogging system in China. The results demonstrate that our scheme provides a much more accurate followee recommendation for a user compared to existing schemes.

关键词： online social networks microblogging followee recommendation simulated annealing ranking

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Generalized association and deep understanding method for big video data processing

Generalized association and deep understanding method for bi...

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2019 IEEE International Conferences on Ubiquitous computing and Communications and Data Science and Computational Intelligence and Smart computing, Networking and services, IUCC/DSCI/SmartCNS 2019

作者： Xu, Lin Wu, Wei Lv, Wanghan Wang, Dong Science and Technology in Information System Engineering Lab Nanjing Research Institute of Electronic Engineering Nanjing China School of Information Science and Engineering University of Jinan China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan China

ISBN: (纸本)9781728152097

In Big Data Era, it is becoming more and more important to timely and efficient processing of massive videos, and mining of the value information contained in them. This paper studies chaotic compressed sensing theory and uses Long-term and short-term memory networks (LSTM) algorithm to generate a summary of the content of video behavior track. It has already to apply the proposed method in target recognition and tracking, and the recognition rate achieves more than 86%. © 2019 IEEE.

关键词： Big data

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An HSR Data Model for Cyborg Insect Research Experiments

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Chinese Journal of Electronics 2018年第4期27卷 680-686页

作者： HONG Hui WANG Xiaoyu ZHU Zhengfei MA Qian GUAN Nan ZHENG Nenggan Key Laboratory of Radio Frequency Circuit and System Hangzhou Dianzi University Qiushi Academy for Advanced Studies Zhejiang University College of Computer Science and Technology Zhejiang University Department of Computing Hong Kong Polytechnic University

Research on cyborg intelligent insects requires the experiment platform to collect data from the distributed sensing models and process the multi-modal signals in real-time. To overcome these issues, we present a novel data model, naming as the Hybrid-synchronizedrealtime(HSR) data model, which can synchronize the hybrid raw data channels by a meta data integration method and process them with a fixed priority scheduling algorithm. Real animal experiments show that the insect-machine experiment platform based on the HSR data model can fully satisfy the requirements of cyborg intelligent insect research, especially in dealing with the technical challenges of data synchronization, real-time processing and hybrid data integration. It provides an efficient approach to implement the experiment platform and thus aid the frontier research on cyborg insects.

关键词： Cyborg intelligent insects Data model Hybrid-synchronized-realtime(HSR)

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Large-scale video compression： recent advances and challenges

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Frontiers of Computer Science 2018年第5期12卷 825-839页

作者： Tao TIAN Hanli WANG Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China Shanghai Engineering Research Center of Industrial Vision Perception & Intelligent Computing Shanghai 200092 China

The evolution of social network and multimedia technologies encourage more and more people to generate and upload visual information, which leads to the generation of large-scale video data. Therefore, preeminent compression technologies are highly desired to facilitate the storage and transmission of these tremendous video data for a wide variety of applications. In this paper, a systematic review of the recent advances for large-scale video compression （LSVC） is presented. Specifically, fast video coding algorithms and effective models to improve video compression efficiency are introduced in detail, since coding complexity and compression efficiency are two important factors to evaluate video coding approaches. Finally, the challenges and fu- ture research trends for LSVC are discussed.

关键词： large-scale video compression fast video coding compression efficiency

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Implementing the matrix multiplication with dfc on kunlun small scale computer 20

Implementing the matrix multiplication with dfc on kunlun sm...

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20th International Conference on Parallel and Distributed computing, Applications and Technologies, PDCAT 2019

作者： Du, Zheng Zhang, Jing Sha, Shihao Luo, Qiuming Department of Computer Science and Technology Tsinghua University China NHPCC/Guangdong Key Laboratory of Popular HPC Guangdong Province Engineering Center of China-made High Performance Data Computing System College of Computer Science Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781728126166

In this paper, we demonstrate a new dataflow platform of DFC, which can handle the successive dataflow computing passes with tagged data. By implementing the matrix multiplication in DFC, we show that DFC can exploit the parallelism automatically with a much simple dataflow graph constructed by DF functions of DFC. Different from the other dataflow execution platform, DFC support multiple worker threads for one dataflow node of DF functions. By running the matrix multiplication program of DFC on Kunlun system, it was verified that DFC get a reasonable speedup for large scale computing for thread number up to 512. © 2019 IEEE.

关键词： Matrix algebra

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Solid-state green-light-emitting upconversion coherent random laser in macroporous LiNbO_3:Er

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Chinese Optics Letters 2018年第1期16卷 62-65页

作者：石凡赵萌贾晨赵宇峰陈胜勇 Key Laboratory of Computer Vision and System of Ministry of Education Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology

A solid-state green-light-emitting upconversion coherent random laser was realized by pumping macroporous erbium-doped lithium niobate with a 980 nm laser. The lasing threshold was determined to be about 40 k W∕cm~*** the threshold, the emission intensity increased sharply with the increasing pump intensity. Moreover, a narrow multi-peaks structure was observed in the green-light-emission band, and the positions of lasing lines were various at different angles. The results were the direct evidences of coherent random lasing emission from macroporous erbium-doped lithium niobate. These phenomena were attributed to the coexistence of upconversion emission and a multiple scattering feedback mechanism.

关键词： Solid-state green-light-emitting upconversion coherent random laser in macroporous LiNbO3:Er LN ETU

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