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珠海市不动产测绘生产系统的设计与实现 预览
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作者 王鉴钦 《地矿测绘》 2019年第1期7-10,共4页
不动产案件数据既是不动产统一登记的重要参考,也可以作为不动产登记的基础性空间数据,为国土资源的各个业务部门的日常业务提供辅助支持。为此,文章介绍了基于Object、OLE和C/S体系结构等技术的珠海市不动产测绘系统的设计与实现。
关键词 不动产登记 OBJECT OLE C/S 测绘生产系统 数据库 功能设计
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Underwater Object Recognition Based on Deep Encoding-Decoding Network 预览
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作者 WANG Xinhua OUYANG Jihong +1 位作者 LI Dayu ZHANG Guang 《中国海洋大学学报:英文版》 SCIE CAS CSCD 2019年第2期376-382,共7页
Ocean underwater exploration is a part of oceanography that investigates the physical and biological conditions for scientific and commercial purposes.And video technology plays an important role and is extensively ap... Ocean underwater exploration is a part of oceanography that investigates the physical and biological conditions for scientific and commercial purposes.And video technology plays an important role and is extensively applied for underwater environment observation.Different from the conventional methods,video technology explores the underwater ecosystem continuously and non-invasively.However,due to the scattering and attenuation of light transport in the water,complex noise distribution and lowlight condition cause challenges for underwater video applications including object detection and recognition.In this paper,we propose a new deep encoding-decoding convolutional architecture for underwater object recognition.It uses the deep encoding-decoding network for extracting the discriminative features from the noisy low-light underwater images.To create the deconvolutional layers for classification,we apply the deconvolution kernel with a matched feature map,instead of full connection,to solve the problem of dimension disaster and low accuracy.Moreover,we introduce data augmentation and transfer learning technologies to solve the problem of data starvation.For experiments,we investigated the public datasets with our proposed method and the state-of-the-art methods.The results show that our work achieves significant accuracy.This work provides new underwater technologies applied for ocean exploration. 展开更多
关键词 DEEP LEARNING transfer LEARNING encoding-decoding UNDERWATER OBJECT OBJECT recognition
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变而求道:国内基础教育学校变革研究述评
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作者 杨润东 《全球教育展望》 CSSCI 北大核心 2019年第4期59-73,共15页
当前我国基础教育学校变革已步入深化阶段,关于学校变革的研究可谓汗牛充栋,对过往研究综而述之有利于研究的深入和理论的新生。国内关于基础教育学校变革的研究主要围绕“如何更好地进行学校变革”这一核心问题,展开为以价值取向、变... 当前我国基础教育学校变革已步入深化阶段,关于学校变革的研究可谓汗牛充栋,对过往研究综而述之有利于研究的深入和理论的新生。国内关于基础教育学校变革的研究主要围绕“如何更好地进行学校变革”这一核心问题,展开为以价值取向、变革主体及其关系、变革对象、变革机制、变革路径及方法为主要研究领域的研究“群带”。纵向来看,过往研究呈现几大发展特点:从把“人”放于变革价值取向的边缘或模糊位置移至核心的价值取向;从单一的变革主体观和割裂的主体关系走向多元一体的变革主体观和多元共生的主体间关系;从以物质和制度为主转向以人和文化为核心的变革对象观;从对变革如何发生发展的简单描述深入到内里的变革机制研究;整个学校变革的方法选择之理从简化、单向、静态式的思维转向复杂性思维。未来要从对学校变革主体、对象、方法和环境的孤立审视走向互动关系的探究,找寻更多变革之道。 展开更多
关键词 学校变革 主体 对象 变革机制 方法论
QUANTIZATION AND TRAINING OF LOW BIT-WIDTH CONVOLUTIONAL NEURAL NETWORKS FOR OBJECT DETECTION
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作者 Penghang Yin Shuai Zhang +1 位作者 Yingyong Qi Jack Xin 《计算数学:英文版》 SCIE CSCD 2019年第3期349-359,共11页
We presen t LBW-Net,an efficient optimization based method for qua nt ization and training of the low bit-width convolutional neural networks(CNNs).Specifically,we quantize the weights to zero or powers of 2 by minimi... We presen t LBW-Net,an efficient optimization based method for qua nt ization and training of the low bit-width convolutional neural networks(CNNs).Specifically,we quantize the weights to zero or powers of 2 by minimizing the Euclidean distance between full-precision weights and quantized weights during backpropagation(weight learning).We characterize the combinatorial nature of the low bit-width quantization problem.For 2-bit(ternary)CNNs,the quantization of N weights can be done by an exact formula in O(N log N)complexity.When the bit-width is 3 and above,we further propose a semi-analytical thresholding scheme with a single free parameter for quantization that is computationally inexpensive.The free parameter is further determined by network retraining and object detection tests.The LBW-Net has several desirable advantages over full-precision CNNs,including considerable memory savings,energy efficiency,and faster deployment.Our experiments on PASCAL VOC dataset show that compared with its 32-bit floating-point counterpart,the performance of the 6-bit LBW-Net is nearly lossless in the object detection tasks,and can even do better in real world visual scenes,while empirically enjoying more than 4× faster deployment. 展开更多
关键词 QUANTIZATION LOW BIT WIDTH deep neural networks Exact and approximate analytical FORMULAS Network training Object detection
我国校园欺凌现象频发的原因分析 预览
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作者 汪红晨 刘箭 《湖北第二师范学院学报》 2019年第3期55-58,共4页
近年来,校园欺凌事件频频发生,引起了社会的广泛关注。校园欺凌不仅造成相关学生生理和心理方面的创伤,不利于他们日后融入社会,也给社会和谐、家庭稳定埋下了较大的隐患。深层次探析我国校园欺凌问题出现的原因,找出问题的根本,对症下... 近年来,校园欺凌事件频频发生,引起了社会的广泛关注。校园欺凌不仅造成相关学生生理和心理方面的创伤,不利于他们日后融入社会,也给社会和谐、家庭稳定埋下了较大的隐患。深层次探析我国校园欺凌问题出现的原因,找出问题的根本,对症下药,才能够有效防治校园欺凌现象的发生。 展开更多
关键词 校园欺凌 对象 原因分析
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BING: Binarized normed gradients for objectness estimation at 300fps
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作者 Ming-Ming Cheng Yun Liu +3 位作者 Wen-Yan Lin Ziming Zhang Paul L.Rosin Philip H.S.Torr 《计算可视媒体(英文版)》 CSCD 2019年第1期3-20,共18页
Training a generic objectness measure to produce object proposals has recently become of significant interest. We observe that generic objects with well-defined closed boundaries can be detected by looking at the norm... Training a generic objectness measure to produce object proposals has recently become of significant interest. We observe that generic objects with well-defined closed boundaries can be detected by looking at the norm of gradients, with a suitable resizing of their corresponding image windows to a small fixed size. Based on this observation and computational reasons, we propose to resize the window to 8 × 8 and use the norm of the gradients as a simple 64 D feature to describe it, for explicitly training a generic objectness measure. We further show how the binarized version of this feature, namely binarized normed gradients(BING), can be used for efficient objectness estimation, which requires only a few atomic operations(e.g., add, bitwise shift, etc.). To improve localization quality of the proposals while maintaining efficiency, we propose a novel fast segmentation method and demonstrate its effectiveness for improving BING’s localization performance, when used in multithresholding straddling expansion(MTSE) postprocessing. On the challenging PASCAL VOC2007 dataset, using 1000 proposals per image and intersectionover-union threshold of 0.5, our proposal method achieves a 95.6% object detection rate and 78.6% mean average best overlap in less than 0.005 second per image. 展开更多
关键词 OBJECT proposals objectness visual ATTENTION CATEGORY agnostic proposals
展览叙事与物的意义--以“湖南人--三湘历史文化陈列”为例
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作者 王思渝 《博物院》 2019年第1期99-103,共5页
从博物馆常设展览的叙事模式出发,提出物的意义不应完全局限在长时段、线性发展式的单一叙事框架内。以此为基础,在对相关理论做出讨论的基础上,以“湖南人--三湘历史文化陈列”为例,试图寻求展览叙事在时间和社会维度上做出平衡的可能性。
关键词 展览叙事 时间线 社会维度
Construct and correlates of basic motor competencies in primary school-aged children
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作者 Christian Herrmann Christopher Heim Harald Seelig 《运动与健康科学:英文版》 SCIE 2019年第1期63-70,共8页
Background: A central aim of physical education is the promotion of basic motor competencies(in German: Motorische Basiskompetenzen;MOBAK), which are prerequisites for children’s active participation in sports cultur... Background: A central aim of physical education is the promotion of basic motor competencies(in German: Motorische Basiskompetenzen;MOBAK), which are prerequisites for children’s active participation in sports culture. This article introduces the MOBAK-1 test instrument for 6-to 8-year-old children and determines the construct validity of this test instrument. In addition, the relationship between MOBAK and motor ability(i.e., strength) as well as body mass index(BMI), sex, and age is investigated.Methods: We analyzed data of 923 first and second graders(422 girls, 501 boys, age = 6.80 ±0.44 years). The children’s basic motor competencies were assessed by the MOBAK-1 test instrument. Besides analyses of frequency, correlation, and variance, 3 confirmatory factor analyses with covariates were performed.Results: We found 2 MOBAK factors consisting of 4 items each. The first factor, locomotion, included the items balancing, rolling, jumping, and side stepping;the second factor, object control, included the items throwing, catching, bouncing, and dribbling. The motor ability strength had a significant influence on the factors locomotion(b = 0.60) and object control(b = 0.50). Older pupils achieved better results than younger pupils on object control(b = 0.29). Boys performed better on object control(b = -0.44), whereas girls achieved better results in locomotion(b = 0.07).Pupils with a high BMI achieved lower performance only on the factor locomotion(b =-0.28).Conclusion: The MOBAK-1 test instrument developed for this study meets psychometric validity demands and is suitable to evaluate effects of sports and physical education. 展开更多
关键词 BMI FACTORIAL validity GROSS MOTOR SKILLS Locomotion Measurement Object control Physical education Strength
粤港澳大湾区城市人文价值链认同研究 预览
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作者 梁建先 《广东技术师范学院学报》 2019年第2期88-93,共6页
粤港澳大湾区在城市文化价值链的融合认同上,具备有天然的条件与优势,首先是认同主体在历史地理、人口语言及特色文化上极具同一性;其次是认同客体在文化、经济、政治的发展方式上的同内质性;再有通过提炼核心文化价值观、加强政府引导... 粤港澳大湾区在城市文化价值链的融合认同上,具备有天然的条件与优势,首先是认同主体在历史地理、人口语言及特色文化上极具同一性;其次是认同客体在文化、经济、政治的发展方式上的同内质性;再有通过提炼核心文化价值观、加强政府引导为主的文化传播影响力,以及加大文化与媒介融合发展的认同创新路径,为实现粤港澳大湾区城市人文价值链的融合与打造大湾区最具竞争的软实力,提供理论与实践的基础。 展开更多
关键词 粤港澳大湾区 城市人文价值链 认同研究
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Performances of different efficiency calibration methods of highpurity- germanium gamma-ray spectrometry in an intercomparison exercise 预览
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作者 Bao-Lu Yang Qiang Zhou +4 位作者 Jing Zhang Shuai-Mo Yao Ze-Shu Li Wen-Hong Li Fei Tuo 《核技术:英文版》 SCIE CAS CSCD 2019年第3期9-14,共6页
This study reports the performances of efficiency calibrations for high-purity-germanium gamma-ray spectrometry using the source-, Laboratory Sourceless Object Calibration Software (LabSOCS)- and ANGLE-based methods i... This study reports the performances of efficiency calibrations for high-purity-germanium gamma-ray spectrometry using the source-, Laboratory Sourceless Object Calibration Software (LabSOCS)- and ANGLE-based methods in an inter-comparison exercise. Although the results of LabSOCS and ANGLE for 241Am emitting lowenergy gamma rays were not very satisfactory, all of the three efficiency calibration methods passed acceptance criteria. The results confirmed the reliability of the calculation codes ANGLE and LabSOCS as alternative efficiency calibration methods in high-purity-germanium gamma spectrometry. This study is likely to promote the further application of the ANGLE and LabSOCS calculation codes in radioactivity measurements. 展开更多
关键词 EFFICIENCY CALIBRATION ANGLE Laboratory Sourceless Object CALIBRATION Software (LabSOCS) GAMMA-RAY spectrometry
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新出土《诗论》以及中国早期诗学的体系化根源
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作者 常森 《北京大学学报:哲学社会科学版》 CSSCI 北大核心 2019年第1期113-123,共11页
新出土《诗论》载录的主要是孔子的论说。它是中国关于文本阐释的早期重要经典,具有《诗经》学和一般诗学的重大意义。联系其他新出儒典,可以看出,早期儒家诗学是在'心''性''物'三者构成的体系框架之上建构的&#... 新出土《诗论》载录的主要是孔子的论说。它是中国关于文本阐释的早期重要经典,具有《诗经》学和一般诗学的重大意义。联系其他新出儒典,可以看出,早期儒家诗学是在'心''性''物'三者构成的体系框架之上建构的'言志''言情'的同一体。'心''性''物'在该体系中的强力凸显,'言志'与'言情'的一体性等,从不同程度上刷新了我们对诗学史的认知。显然,《诗论》以及其他相关早期儒典在大约两千年间的突然'缺席',以《诗序》《毛传》《郑笺》为核心的强大的汉唐《诗经》学形态模式的确立,以及《诗序》碎片化地承继孔子诗学所产生的误导作用,造就了后人对中国早期诗学的巨大认知偏差。 展开更多
关键词 孔子
基于Object-Z生成Python代码的研究 预览
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作者 袁鼎 刘振宇 《电子技术与软件工程》 2019年第5期234-235,共2页
在本文中,我们将提出一种从OZ到Python的映射去验证这些规范。在这个映射中,包括前置条件、后置条件和变量都将被验证,这些都是建立在使用lambda函数(以下简称L函数)和Python的编辑器上的。本研究发现Python对于开发从OZ映射到Python的... 在本文中,我们将提出一种从OZ到Python的映射去验证这些规范。在这个映射中,包括前置条件、后置条件和变量都将被验证,这些都是建立在使用lambda函数(以下简称L函数)和Python的编辑器上的。本研究发现Python对于开发从OZ映射到Python的函数库来说是一种相对完美的语言。 展开更多
关键词 OBJECT-Z PYTHON 面向对象编程 契约式设计
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现代大学文化治理:对象、形式与组织的三维向度论析 预览
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作者 张琴 《江苏高教》 CSSCI 北大核心 2019年第3期62-65,共4页
在完善和提升现代大学治理的进程中,文化发挥着越来越重要的作用。当前,中国大学文化治理面临着一系列新的挑战,推动大学文化治理现代化成为“双一流”建设的重要一环,必须紧扣对象、形式与组织的三维向度,强化以人为本,重视多渠道多方... 在完善和提升现代大学治理的进程中,文化发挥着越来越重要的作用。当前,中国大学文化治理面临着一系列新的挑战,推动大学文化治理现代化成为“双一流”建设的重要一环,必须紧扣对象、形式与组织的三维向度,强化以人为本,重视多渠道多方向提升文化治理水平,实现高等教育的协调与善治。 展开更多
关键词 现代大学文化 文化治理 治理对象 治理形式 治理组织
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“语义三角”的认知拓扑性探析
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作者 张雪梅 刘宇红 《外语学刊》 CSSCI 北大核心 2019年第2期8-14,共7页
认知拓扑学视域下,“语义三角”中的3个部分分别构成客观、概念和语言3个拓扑空间。3个空间不仅内部具有拓扑性,而且它们之间还具有层层推进的拓扑关系。拓扑性是思维对客观世界进行范畴化的需要,是语言符号有限性和经济性的要求,也是... 认知拓扑学视域下,“语义三角”中的3个部分分别构成客观、概念和语言3个拓扑空间。3个空间不仅内部具有拓扑性,而且它们之间还具有层层推进的拓扑关系。拓扑性是思维对客观世界进行范畴化的需要,是语言符号有限性和经济性的要求,也是意义形成的原动力与必然过程。由于认知主体对拓扑维度、视角等的选择差异,拓扑变换的过程中会出现拓扑深度与广度的差异。3个空间之间并非镜像式一一对应的关系,从客观到概念空间以及从概念到语言空间体现直接拓扑关系,而客观与语言空间之间则是间接拓扑关系。 展开更多
关键词 语义三角 认知拓扑 拓扑性 客观 概念 语言
论人工智能的法律地位 预览
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作者 刘洪华 《政治与法律》 CSSCI 北大核心 2019年第1期11-21,共11页
人工智能拥有类似人类的智能,但是并未发展出人类理性,也不能为自己立法,不可取得类似自然人的法律主体地位。人工智能虽然具有某些超越人类能力的强大工具,但是为其拟制一个法律主体并无实益,不可赋予其类似法人的法律主体地位。人工... 人工智能拥有类似人类的智能,但是并未发展出人类理性,也不能为自己立法,不可取得类似自然人的法律主体地位。人工智能虽然具有某些超越人类能力的强大工具,但是为其拟制一个法律主体并无实益,不可赋予其类似法人的法律主体地位。人工智能超强的智能蕴含巨大的风险,必须处于人类的支配和控制之下,只能是法律关系客体而非主体。鉴于人工智能的智能性和自主性,可以将高度智能化的人工智能作为客体中的特殊物,予以特殊的法律规制。 展开更多
关键词 人工智能 主体 客体 理性
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莱布尼茨物体哲学系统与力的概念问题——基于对物体和运动现象性的阐释
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作者 齐明皓 《系统科学学报》 CSSCI 北大核心 2019年第2期19-22,48共5页
G.W.莱布尼茨是近代西方哲学史上最卓越的先驱之一。他从不同角度对“物体是实体还是现象”的哲学问题的阐释,使得其哲学的全景系统呈现出较大的差异。他一方面认为物体作为现象是意识派生的存在,物体具有的实在性处于意识具有的统一性... G.W.莱布尼茨是近代西方哲学史上最卓越的先驱之一。他从不同角度对“物体是实体还是现象”的哲学问题的阐释,使得其哲学的全景系统呈现出较大的差异。他一方面认为物体作为现象是意识派生的存在,物体具有的实在性处于意识具有的统一性之下。另一方面,他把物理学上的物体概念也作为实体来积极地进行解释。他关于物体概念的定位使得其哲学系统难以为人所理解。从莱布尼茨物体哲学出发,通过系统探讨他的“力”的概念的变迁,可以发现莱布尼茨对“力”的概念的二元化的积极评价阐明了物体具有的两义性,即实在性和现象性。而运动作为现象的性质也拓展了他所处时代力学的学问领域。在此意义上,“力”的概念问题的深化于莱布尼茨而言是划时代的成果。对“力”的概念问题的理解也有助于我们洞悉其物体哲学系统的精髓。 展开更多
关键词 物体哲学 力的概念 现象性
以含混的方式去交叠 预览
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作者 黄斌 李凝玉 《当代美术家》 2019年第1期64-67,共4页
当边界被巧妙而自然地稀释,生长出来的是更加自由而内涵丰富的作品。黄斌的创作开始逼近、突破传统版画的边界,再加上他想讨论的多元的话题:城市、材料、物、场域……一如作品名“Ambiguity”所表达的含混和微妙。早已融入自身的版画的... 当边界被巧妙而自然地稀释,生长出来的是更加自由而内涵丰富的作品。黄斌的创作开始逼近、突破传统版画的边界,再加上他想讨论的多元的话题:城市、材料、物、场域……一如作品名“Ambiguity”所表达的含混和微妙。早已融入自身的版画的概念、思维逻辑和工作方式成为这一探索的助力而非屏障,内化为极具特色的个人语汇。 展开更多
关键词 边界 场域
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赋体与图像关联的文学原理 预览
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作者 许结 《天中学刊》 2019年第2期53-59,共7页
赋体与图像的关联或类比,其实质是赋与画在叙事方面有着一些共通的文学原理。从"体物"的角度来看,历代赋论对赋语的批评相对集中于"物尽其态"的描绘特色,表现"赋像班形"的审美取向;从"述事"的... 赋体与图像的关联或类比,其实质是赋与画在叙事方面有着一些共通的文学原理。从"体物"的角度来看,历代赋论对赋语的批评相对集中于"物尽其态"的描绘特色,表现"赋像班形"的审美取向;从"述事"的角度来看,赋以写物为体制,然必明于事而尚其辞,故赋体文学明"事物"(观象)与明"事情""事理"亦相契合;从"观仪"的角度来看,赋体给人以图像化的阅读感受,在于近似视觉文本的可"观",赋可观作者之才学与风采,可观社会之礼仪与制度。《文心雕龙》中的"随物""图色"与"形文",也可作为解释赋体与图像关联之文学原理的依据。 展开更多
关键词 赋体 图像 关联 体物 述事 观仪
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Multi-scale object detection by top-down and bottom-up feature pyramid network 预览
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作者 ZHAO Baojun ZHAO Boya +2 位作者 TANG Linbo WANG Wenzheng WU Chen 《系统工程与电子技术:英文版》 SCIE EI CSCD 2019年第1期1-12,共12页
While moving ahead with the object detection technology, especially deep neural networks, many related tasks, such as medical application and industrial automation, have achieved great success. However, the detection ... While moving ahead with the object detection technology, especially deep neural networks, many related tasks, such as medical application and industrial automation, have achieved great success. However, the detection of objects with multiple aspect ratios and scales is still a key problem. This paper proposes a top-down and bottom-up feature pyramid network (TDBU-FPN), which combines multi-scale feature representation and anchor generation at multiple aspect ratios. First, in order to build the multi-scale feature map, this paper puts a number of fully convolutional layers after the backbone. Second, to link neighboring feature maps, top-down and bottom-up flows are adopted to introduce context information via top-down flow and supplement suboriginal information via bottom-up flow. The top-down flow refers to the deconvolution procedure, and the bottom-up flow refers to the pooling procedure. Third, the problem of adapting different object aspect ratios is tackled via many anchor shapes with different aspect ratios on each multi-scale feature map. The proposed method is evaluated on the pattern analysis, statistical modeling and computational learning visual object classes (PASCAL VOC) dataset and reaches an accuracy of 79%, which exhibits a 1.8% improvement with a detection speed of 23 fps. 展开更多
关键词 convolutional neural NETWORK (CNN) FEATURE PYRAMID NETWORK (FPN) object detection deconvolution.
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Recurrent 3D attentional networks for end-to-end active object recognition
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作者 Min Liu Yifei Shi +3 位作者 Lintao Zheng Kai Xu Hui Huang Dinesh Manocha 《计算可视媒体(英文版)》 CSCD 2019年第1期91-103,共13页
Active vision is inherently attention-driven:an agent actively selects views to attend in order to rapidly perform a vision task while improving its internal representation of the scene being observed.Inspired by the ... Active vision is inherently attention-driven:an agent actively selects views to attend in order to rapidly perform a vision task while improving its internal representation of the scene being observed.Inspired by the recent success of attention-based models in 2D vision tasks based on single RGB images, we address multi-view depth-based active object recognition using an attention mechanism, by use of an end-to-end recurrent 3D attentional network. The architecture takes advantage of a recurrent neural network to store and update an internal representation. Our model,trained with 3D shape datasets, is able to iteratively attend the best views targeting an object of interest for recognizing it. To realize 3D view selection, we derive a 3D spatial transformer network. It is dierentiable,allowing training with backpropagation, and so achieving much faster convergence than the reinforcement learning employed by most existing attention-based models. Experiments show that our method, with only depth input, achieves state-of-the-art next-best-view performance both in terms of time taken and recognition accuracy. 展开更多
关键词 active object RECOGNITION RECURRENT NEURAL network next-best-view 3D ATTENTION
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