检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Tanaka, Takumi S. Silverman, John D. Shimasaku, Kazuhiro Arita, Junya Akins, Hollis B. Inayoshi, Kohei Ding, Xuheng Onoue, Masafusa Liu, Zhaoxuan Casey, Caitlin M. Lambrides, Erini Kokorev, Vasily Jin, Shuowen Faisst, Andreas L. Drakos, Nicole Shen, Yue Li, Junyao Zhuang, Mingyang Fei, Qinyue Ito, Kei Ren, Wenke Matsui, Suin Ando, Makoto Hatano, Shun Fujii, Michiko S. Kartaltepe, Jeyhan S. Koekemoer, Anton M. Liu, Daizhong McCracken, Henry Joy Rhodes, Jason Robertson, Brant E. Franco, Maximilien Andika, Irham T. Cloonan, Aidan P. Fan, Xiaohui Gozaliasl, Ghassem Harish, Santosh Hayward, Christopher C. Huertas-Company, Marc Kakkad, Darshan Kinugawa, Tomoya Roy, Namrata Shuntov, Marko Talia, Margherita Toft, Sune Vijayan, Aswin P. Zhang, Yiyang The University of Tokyo Institutes for Advanced Study The University of Tokyo Kashiwa Chiba277-8583 Japan Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan UTIAS The University of Tokyo Kashiwa Chiba277-8583 Japan Center for Astrophysical Sciences Department of Physics and Astronomy Johns Hopkins University BaltimoreMD21218 United States Research Center for the Early Universe Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Department of Astronomy The University of Texas at Austin 2515 Speedway Boulevard Stop C1400 AustinTX78712 United States Kavli Institute for Astronomy and Astrophysics Peking University Beijing100871 China School of Physics and Technology Wuhan University Wuhan430072 China Denmark NASA-Goddard Space Flight Center Code 662 GreenbeltMD20771 United States Kapteyn Astronomical Institute University of Groningen Groningen9700 AV Netherlands DTU Space Technical University of Denmark Elektrovej Building 328 Kgs. Lyngby2800 Denmark Caltech/IPAC 1200 E. California Blvd PasadenaCA91125 United States Department of Physics and Astronomy University of Hawaii Hilo 200 W Kawili St. HiloHI96720 United States Department of Astronomy University of Illinois at Urbana-Champaign UrbanaIL61801 United States National Center for Supercomputing Applications University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Astronomy School of Physics Peking University Beijing100871 China CAS Key Laboratory for Research in Galaxies and Cosmology Department of Astronomy University of Science and Technology of China Anhui Hefei230026 China School of Astronomy and Space Science University of Science and Technology of China Hefei230026 China National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Osawa 2-21-1 Mitaka Tokyo181-8588 Japan Laboratory for Multiwave

"Little Red Dots" (LRDs) are an abundant high-redshift population newly discovered by the James Webb Space Telescope (JWST). They are characterized by a red color in the rest-frame optical band, compact morphology, and broad Balmer emission lines (FWHM >∼ 1000 km s−1) that suggest an AGN nature. Using a method of pixel-by-pixel color selection and relaxing the compactness criteria, we identify three of the first dual LRD candidates in the COSMOS-Web survey with projected separations of 0.′′2-0.′′4 (1-2 pkpc at their photometric redshifts). A comparison between existing LRD samples and mock data reveals that the projected separations of these dual LRD candidates are unlikely to result from chance projections of objects at different redshifts. In one case (CW-B5-15958), the dual LRD includes two bright sources (mF444W = 24.3 and 24.8) with characteristic V-shape spectral energy distribution (SEDs) and photometric redshifts consistent with each other. We find that CW-B5-15958 has a faint off-centered component and a companion galaxy. In the other two dual systems, the brighter LRD exhibits a V-shape SED, while the fainter LRD (mF444W>∼ 26) is undetected in both F115W and F150W. These discoveries suggest that the angular auto-correlation function (ACF) of LRDs exhibits a significant excess (∼ 3 × 102 times) on sub-arcsec (kilo-parsec) separations compared to the extrapolation of a power-law ACF of JWST-found AGNs measured over 10′′-100′′. Follow-up spectroscopic confirmation of their redshifts and the construction of a larger sample are essential to advance our understanding of the evolution of supermassive black holes and the importance of mergers in the early universe. © 2024, CC BY.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of T-Hash Tree in Main Memory Data Base

Design and Implementation of T-Hash Tree in Main Memory Data...

引用

International Conference on Image, Vision and Computing (ICIVC)

作者： Zhiqiang Hu Meiqi Hu General Department of network and information security Beijing Institute of Computer Technology and Applications Beijing China Technical service center Shenzhou General Data Technology Co. Ltd. Beijing China

ISBN: (纸本)9781538649923

There are some shortcomings for the cache sensitivity of the index in main memory database, so a new index structure is proposed. T -tree index is studied individually ever before, so as Hash index. Combined with the analysis of the two index structure, a new index structure called the T-Hash tree is introduced. Through analyzing the times of the T -Hash tree cache sensitive and testing the performance of the query, insert, delete operation, the results show that the T -Hash tree can effectively reduce the times of cache sensitive, and as the amount of the data is large, the query, insert, delete efficiency of the T -Hash tree is higher than the T tree.

关键词： Vegetation Indexes Query processing Electronic mail Memory management Keyword search

来源：评论

学校读者我要写书评

暂无评论

SSBC 2020: Sclera Segmentation Benchmarking Competition in the Mobile Environment

SSBC 2020: Sclera Segmentation Benchmarking Competition in t...

引用

IEEE International Joint Conference on Biometrics (IJCB)

作者： M. Vitek A. Das Y. Pourcenoux A. Missler C. Paumier S. Das I. De Ghosh D. R. Lucio L. A. Zanlorensi D. Menotti F. Boutros N. Damer J. H. Grebe A. Kuijper J. Hu Y. He C. Wang H. Liu Y. Wang Z. Sun D. Osorio-Roig C. Rathgeb C. Busch J. Tapia A. Valenzuela G. Zampoukis L. Tsochatzidis I. Pratikakis S. Nathan R. Suganya V. Mehta A. Dhall K. Raja G. Gupta J. N. Khiarak M. Akbari-Shahper F. Jaryani M. Asgari-Chenaghlu R. Vyas S. Dakshit P. Peer U. Pal V. Štruc University of Ljubljana (UL SI) Indian Statistical Institute (lSI IN) Grenoble Institute of Technology (INP FR) Ècole Nationale Supérieure de 1’Èlectronique et de ses Applications (ENSEA FR) University of Engineering and Management (UEM IN) Barrackpore Rastraguru Surendranath College (BRSNC IN) Federal University of Paraná (UFPR BR) Technische Universität Darmstadt (TUD DE) Fraunhofer Institute for Computer Graphics Research (IGD DE) Chinese Academy of Sciences (CAS CN) Beijing University of Civil Engineering and Architecture (BUCEA CN) Hochschule Darmstadt (HDA DE) Universidad de Santiago (USACH CL) TOC Biometrics (CL) Democritus University of Thrace (DUTH GR) Couger Inc. (JP) Thiagarajar College of Engineering (TCE IN) Indian Institute of Technology Ropar (IIT-RPR IN) Monash University (MU AU) Norwegian University of Science and Technology (NTNU NO) Warsaw University of Technology (WUT PL) Tabriz University (TU IR) Arak University (AU IR) Bennet University (BU IN) Calcutta Institute of Engineering and Management Maulana Abul Kalam University of Technology (MAKAUT IN) University of Texas at Dallas (UTD US

ISBN: (数字)9781728191867

ISBN: (纸本)9781728191874

The paper presents a summary of the 2020 Sclera Segmentation Benchmarking Competition (SSBC), the 7th in the series of group benchmarking efforts centred around the problem of sclera segmentation. Different from previous editions, the goal of SSBC 2020 was to evaluate the performance of sclera-segmentation models on images captured with mobile devices. The competition was used as a platform to assess the sensitivity of existing models to i) differences in mobile devices used for image capture and ii) changes in the ambient acquisition conditions. 26 research groups registered for SSBC 2020, out of which 13 took part in the final round and submitted a total of 16 segmentation models for scoring. These included a wide variety of deep-learning solutions as well as one approach based on standard image processing techniques. Experiments were conducted with three recent datasets. Most of the segmentation models achieved relatively consistent performance across images captured with different mobile devices (with slight differences across devices), but struggled most with low-quality images captured in challenging ambient conditions, i.e., in an indoor environment and with poor lighting.

关键词： Image segmentation Mobile handsets Performance evaluation Benchmark testing Training Lighting Iris recognition

来源：评论

学校读者我要写书评

暂无评论

Spatiotemporal Variations of Aksai Chin Lake and its influencing factors during 1972-2018

引用

IOP Conference Series: Earth and Environmental Science 2021年第1期783卷

作者： Wei Yan Ziyun Jiang Feng Zhou Jia Ning Shuangshuang Hou Jian Wang Rumeng Han Minghua Liu School of Urban and Planning Yancheng Teachers University Yancheng Jiangsu 224007 China School of Geographic Sciences Xinyang Normal University Xinyang Henan 46400 China College of Computer and Information Technology Xinyang Normal University Xinyang Henan 46400 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China College of Life Sciences Guizhou University Guiyang Guizhou 550001 China

In the context of increasing lake expansion on the Tibetan Plateau, which is sensitive to climate change, it is of great significance to strengthen the research on the characteristics of lake change and its response to climate change. This paper was designed to investigate the spatiotemporal variations of Aksai Chin Lake (ACL), a typical large lake on the Tibetan Plateau, by using Landsat MSS/TM/ETM+/OLI images during 1972-2018, and to quantitatively discuss the effects of climate on lake changes based on meteorological data from Shiquanhe station. During 1961-2018, annual mean air temperature and precipitation in this region increased at rates of 0.44 °C/decade and 1.35 mm/decade, respectively, with a mutation point of 1999 for temperature, while evaporation decreased at the rate of -54.3 mm/decade, with two mutation points in 1972 and 2014, respectively. The area of ACL had increased at an average rate of 2.51 km2 per year, with a fluctuation of 'slight expansion – shrinkage – rapid expansion – slight expansion – rapid expansion' during 1972-2018. Controlled by the topography, the ACL expanded to the southeast by 3851.6 m in total. In terms of the lake area response to climate change, air temperature and evaporation were the main factors affecting ACL area directly, while precipitation mainly regulated ACL by the indirect effect through air temperature and evaporation. Generally, rising air temperature, increasing precipitation and decreasing evaporation all contribute to promote the expansion of ACL.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Distant supervision for relation extraction with linear attenuation simulation and non-IID relevance embedding

arXiv

引用

arXiv 2018年

作者： Yuan, Changsen Huang, Heyan Feng, Chong Liu, Xiao Wei, Xiaochi Department of Computer Science Beijing Institute of Technology China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications China Baidu Inc. China

Distant supervision for relation extraction is an efficient method to reduce labor costs and has been widely used to seek novel relational facts in large corpora, which can be identified as a multi-instance multi-label problem. However, existing distant supervision methods suffer from selecting important words in the sentence and extracting valid sentences in the bag. Towards this end, we propose a novel approach to address these problems in this paper. Firstly, we propose a linear attenuation simulation to reflect the importance of words in the sentence with respect to the distances between entities and words. Secondly, we propose a non-independent and identically distributed (non-IID) relevance embedding to capture the relevance of sentences in the bag. Our method can not only capture complex information of words about hidden relations, but also express the mutual information of instances in the bag. Extensive experiments on a benchmark dataset have well-validated the effectiveness of the proposed method. Copyright © 2018, The Authors. All rights reserved.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

BIT at SemEval-2017 Task 1: Using Semantic Information Space to Evaluate Semantic Textual Similarity 11

BIT at SemEval-2017 Task 1: Using Semantic Information Space...

引用

11th International Workshop on Semantic Evaluations, SemEval 2017, co-located with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017

作者： Wu, Hao Huang, Heyan Jian, Ping Guo, Yuhang Su, Chao Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications School of Computer Science Beijing Institute of Technology Beijing China

ISBN: (纸本)9781945626555

This paper presents three systems for semantic textual similarity (STS) evaluation at SemEval-2017 STS task. One is an unsupervised system and the other two are supervised systems which simply employ the unsupervised one. All our systems mainly depend on the semantic information space (SIS), which is constructed based on the semantic hierarchical taxonomy in WordNet, to compute non-overlapping information content (IC) of sentences. Our team ranked 2nd among 31 participating teams by the primary score of Pearson correlation coefficient (PCC) mean of 7 tracks and achieved the best performance on Track 1 (AR-AR) dataset. © 2017 Association for Computational Linguistics

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Outcomes from a Workshop on a National Center for Quantum Education

arXiv

引用

arXiv 2024年

作者： Barnes, Edwin Bennett, Michael B. Boltasseva, Alexandra Borish, Victoria Brown, Bennett Carr, Lincoln D. Ceballos, Russell R. Dukes, Faith Easton, Emily W. Economou, Sophia E. Edwards, E.E. Finkelstein, Noah D. Fracchiolla, C. Franklin, Diana Freericks, J.K. Goss, Valerie Hannum, Mark Holincheck, Nancy Kelly, Angela M. Lanes, Olivia Lewandowski, H.J. Matsler, Karen Jo Mercurio, Emily Montaño, Inès Murdock, Maajida Peltz, Kiera Perron, Justin K. Richardson, Christopher J.K. Rosenberg, Jessica L. Ross, Richard S. Ryu, Minjung Samuel, Raymond E. Schrode, Nicole Schwamberger, Susan Searles, Thomas A. Singh, Chandralekha Tingle, Alexandra Zwickl, Benjamin M. Department of Physics Virginia Tech Center for Quantum Information Science and Engineering Virginia Tech 850 West Campus Drive BlacksburgVA24061 United States Q-SEnSE NSF QLCI University of Colorado 440 UCB BoulderCO80301 United States Elmore Family School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue Quantum Science and Engineering Institute Purdue University 610 Purdue Mall West LafayetteIN47907 United States Quantum Science Center A National Quantum Information Science Research Center of The U.S. Department of Energy Oak Ridge National Laboratory 1 Bethel Valley Road Oak RidgeTN37830 United States JILA National Institute of Standards and Technology the University of Colorado BoulderCO80309 United States Department of Physics University of Colorado 390 UCB BoulderCO80309 United States QuSTEAM 510 Ronalds St. Iowa CityIA52245 United States Quantum Engineering Program Department of Physics Colorado School of Mines 1523 Illinois St. GoldenCO80401 United States QuSTEAM Non-Profit Wilbur Wright College City Colleges of Chicago 4300 N Narragansett Ave ChicagoIL60634 United States Government and Community Relations Office - K-12 Programs Lawrence Berkeley National Laboratory 1 Cyclotron Road BerkeleyCA United States Chicago Quantum Exchange 5235 S. Harper Court ChicagoIL60615 United States Department of Physics Virginia Tech 850 West Campus Drive BlacksburgVA24060 United States Department of Electrical and Computer Engineering Duke Quantum Center Duke University Duke University 130 Hudson Hall DurhamNC27708 United States American Physical Society 555 12th St. NW WashingtonDC20004 United States Computer Science University of Chicago 5730 S. Ellis Ave. ChicagoIL60637 United States Department of Physics Georgetown University 552 Reiss Science Building WashingtonDC20057 United States Chemistry Physics and Engineering Studies Chicago State University 9501 S. King Drive WSC 309 ChicagoIL606

In response to numerous programs seeking to advance quantum education and workforce development in the United States, experts from academia, industry, government, and professional societies convened for a National Science Foundation-sponsored workshop in February 2024 to explore the benefits and challenges of establishing a national center for quantum education. Broadly, such a center would foster collaboration and build the infrastructure required to develop a diverse and quantum-ready workforce. The workshop discussions centered around how a center could uniquely address gaps in public, K-12, and undergraduate quantum information science and engineering (QISE) education. Specifically, the community identified activities that, through a center, could lead to an increase in student awareness of quantum careers, boost the number of educators trained in quantum-related subjects, strengthen pathways into quantum careers, enhance the understanding of the U.S. quantum workforce, and elevate public engagement with QISE. Core proposed activities for the center include professional development for educators, coordinated curriculum development and curation, expanded access to educational laboratory equipment, robust evaluation and assessment practices, network building, and enhanced public engagement with quantum science. © 2024, CC BY.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Erratum: Towards a muon collider

引用

The European Physical Journal C 2024年第1期84卷 1-4页

作者： Accettura, Carlotta Adams, Dean Agarwal, Rohit Ahdida, Claudia Aimè, Chiara Amapane, Nicola Amorim, David Andreetto, Paolo Anulli, Fabio Appleby, Robert Apresyan, Artur Apyan, Aram Arsenyev, Sergey Asadi, Pouya Mahmoud, Mohammed Attia Azatov, Aleksandr Back, John Balconi, Lorenzo Bandiera, Laura Barlow, Roger Bartosik, Nazar Barzi, Emanuela Batsch, Fabian Bauce, Matteo Berg, J. Scott Bersani, Andrea Bertarelli, Alessandro Bertolin, Alessandro Black, Kevin Boattini, Fulvio Bogacz, Alex Bonesini, Maurizio Bordini, Bernardo Bottaro, Salvatore Bottura, Luca Braghieri, Alessandro Breschi, Marco Bruhwiler, Natalie Buffat, Xavier Buonincontri, Laura Burrows, Philip N. Burt, Graeme Buttazzo, Dario Caiffi, Barbara Calviani, Marco Calzaferri, Simone Calzolari, Daniele Capdevilla, Rodolfo Carli, Christian Casaburo, Fausto Casarsa, Massimo Castelli, Luca Catanesi, Maria Gabriella Cavallucci, Lorenzo Cavoto, Gianluca Celiberto, Francesco Giovanni Celona, Luigi Cerri, Alessandro Cesarini, Gianmario Cesarotti, Cari Chachamis, Grigorios Chance, Antoine Chen, Siyu Chien, Yang-Ting Chiesa, Mauro Colaleo, Anna Collamati, Francesco Collazuol, Gianmaria Costa, Marco Craig, Nathaniel Curatolo, Camilla Curtin, David Da Molin, Giacomo Dam, Magnus Damerau, Heiko Dasu, Sridhara de Blas, Jorge De Curtis, Stefania De Matteis, Ernesto De Rosa, Stefania Delahaye, Jean-Pierre Denisov, Dmitri Denizli, Haluk Densham, Christopher Dermisek, Radovan Di Luzio, Luca Di Meco, Elisa Di Micco, Biagio Dienes, Keith Diociaiuti, Eleonora Dorigo, Tommaso Dudarev, Alexey Edgecock, Robert Errico, Filippo Fabbrichesi, Marco Farinon, Stefania Ferrari, Anna Somoza, Jose Antonio Ferreira Filthaut, Frank Fiorina, Davide Fol, Elena Forslund, Matthew Franceschini, Roberto Ximenes, Rui Franqueira Gabrielli, Emidio Gallinaro, Michele Garosi, Francesco Giambastiani, Luca Gianelle, Alessio Gilardoni, Simone Giove, Dario Augusto Giraldin, Carlo Glioti, Alfredo Greco, Mario Greljo, Admir Groeber, Ramona Grojean, Christophe Grudiev, Alexej Gu, Jiayin Han, Chengcheng Han, T Organisation Européenne pour la Recherche Nucléaire (CERN) Geneva Switzerland STFC Rutherford Appleton Laboratory (RAL) Oxford UK Computer Science Department University of California (UC) Berkeley USA Dipartimento di Fisica Università di Pavia Pavia Italy INFN Sezione di Pavia Pavia Italy INFN Sezione di Torino Turin Italy Dipartimento di Fisica Università di Torino Turin Italy INFN Sezione di Padova Padua Italy INFN Sezione di Roma Rome Italy School of Physics and Astronomy University of Manchester Manchester UK Fermi National Accelerator Laboratory Batavia USA Department of Physics Brandeis University Waltham USA IRFU CEA University Paris-Saclay Gif-sur-Yvette France Center for Theoretical Physics Massachusetts Institute of Technology Cambridge USA Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt SISSA International School for Advanced Studies Trieste Italy INFN Sezione di Trieste Trieste Italy Department of Physics University of Warwick Coventry UK Dipartimento di Fisica Università di Milano Milan Italy INFN Laboratori Acceleratori e Superconduttività Applicata (LASA) Milan Italy INFN Sezione di Ferrara Ferrara Italy School of Computing and Engineering The University of Huddersfield Huddersfield UK Ohio State University Columbus USA Brookhaven National Laboratory Upton USA INFN Sezione di Genova Genoa Italy University of Wisconsin Wisconsin USA Center for Advanced Studies of Accelerators Jefferson Lab Newport News USA INFN Sezione di Milano Bicocca Milan Italy Dipartimento di Fisica Università di Milano Bicocca Milan Italy Scuola Normale Superiore Pisa Italy INFN Sezione di Pisa Pisa Italy Dipartimento di Ingegneria dell’Energia Elettrica e dell’Informazione Università di Bologna Bologna Italy INFN Sezione di Bologna Bologna Italy Department of Physics University of California (UC) Berkeley USA Dipartimento di Fisica e Astronomia Università di Padova Padoa Italy John Adams Institute University of O

来源：评论

学校读者我要写书评

暂无评论

DESIGN AND IMPLEMENTATION OF SMART COOKING BASED ON AMAZON ECHO

arXiv

引用

arXiv 2018年

作者： Xiaoguang, Lin Yong, Yang Ju, Zhang University of Chinese Academy of Sciences Beijing China Chengdu Computer Applications Institute Chinese Academy of Sciences Chengdu China Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China

Smart cooking based on Amazon Echo uses the internet of things and cloud computing to assist in cooking food. People may speak to Amazon Echo during the cooking in order to get the information and situation of the cooking. Amazon Echo recognizes what people say, then transfers the information to the cloud services, and speaks to people the results that cloud services make by querying the embedded cooking knowledge and achieving the information of intelligent kitchen devices online. An intelligent food thermometer and its mobile application are well-designed and implemented to monitor the temperature of cooking food. Copyright © 2018, The Authors. All rights reserved.

关键词： Web services

来源：评论

学校读者我要写书评

暂无评论

Query translation based on visual information

Query translation based on visual information

引用

International Workshop on Advanced Computational Intelligence (IWACI)

作者： Jiao Zhang Yonggang Huang Qingzhao Jiang Wenpeng Lu Hualei Shen Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing Institute of Technology Beijing China School of Information QiLu University of Technology JiNan China College of Computer and Information Engineering Henan Normal University Xinxiang China

In the field of cross language information retrieval, how to translate the query into the target language, namely query translation, is a fundamental problem. Because of the ambiguity phenomenon, query translation is always a challenge. Existing researches always rely on mining the text information, such as the contextual relationship or word occurrence. Different from existing research efforts, in this paper, we address the query translation issue by mining the visual information of images, and a new query translation method based on visual information (QTVI) is proposed. QTVI has three steps: image search, image set denoising, and translation candidate selection. In step 1, the query and candidate translation are associated with corresponding image set via image search. Since the resulted image sets from step 1 may be unclean, in step 2, we de-noise the image sets via clustering strategy. Finally, in step 3, the final translation is selected from candidates by constructing multi-class classifier based on cleaned image sets. Empirical experiments show that QTVI outperforms Baidu Translation and Google Translation for the query translation task.

关键词： Visualization Noise reduction Dictionaries Semantics Google Frequency modulation Feature extraction

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：