检索结果-内蒙古大学图书馆

arXiv 2022年

作者： Aldulijan, Ibrahim Beal, Jacob Billerbeck, Sonja Bouffard, Jeff Chambonnier, Gaël Delkis, Nikolaos Guerreiro, Isaac Holub, Martin Ross, Paul Selvarajah, Vinoo Sprent, Noah Vidal, Gonzalo Vignoni, Alejandro Systems Engineering Stevens Institute of Technology 1 Castle Point Terrace HobokenNJ07030 United States Intelligent Software & Systems Raytheon BBN Technologies 10 Moulton Street CambridgeMA02138 United States Molecular Microbiology Groningen Biomolecular Sciences and Biotechnology Institute University of Groningen Nijenborgh 7 Groningen9747 AG Netherlands Centre for Applied Synthetic Biology Department of Biology Concordia University 7141 Sherbrooke Street West MontréalQCH4B 1R6 Canada Department of Biological Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Plant and Environmental Biotechnology Laboratory Department of Biochemistry and Biotechnology University of Thessaly Viopolis Mezourlo Larissa41500 Greece iGEM Foundation 45 Prospect Street CambridgeMA02139 United States Delft University of Technology Van der Maasweg 9 2629 HZ Netherlands BioStrat Marketing 9965 Harbour Lake Circle Boynton BeachFL33437 United States Department of Chemical Engineering Imperial College London South Kensington Campus Exhibition Road SW7 2AZ United Kingdom Research Group School of Computing Newcastle University Devonshire Building Devonshire Terrace Newcastle Upon TyneNE1 7RU United Kingdom Synthetic Biology and Biosystems Control Lab Instituto de Automatica e Informatica Industrial Universitat Politecnica de Valencia Camino de Vera s/n Valencia46022 Spain

Synthetic biologists have made great progress over the past decade in developing methods for modular assembly of genetic sequences and in engineering biological systems with a wide variety of functions in various contexts and organisms. However, current paradigms in the field entangle sequence and functionality in a manner that makes abstraction difficult, reduces engineering flexibility, and impairs predictability and design reuse. Functional Synthetic Biology aims to overcome these impediments by focusing the design of biological systems on function, rather than on sequence. This reorientation will decouple the engineering of biological devices from the specifics of how those devices are put to use, requiring both conceptual and organizational change, as well as supporting software tooling. Realizing this vision of Functional Synthetic Biology will allow more flexibility in how devices are used, more opportunity for reuse of devices and data, improvements in predictability, and reductions in technical risk and cost. © 2022, CC BY.

关键词： Biological systems

来源：评论

学校读者我要写书评

暂无评论

Can Forensic Detectors Identify GAN Generated Images?

Can Forensic Detectors Identify GAN Generated Images?

引用

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

作者： Haodong Li Han Chen Bin Li Shunquan Tan Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781728102436;9789881476852

Generative adversarial network (GAN) has shown its powerful capability in generating photorealistic images. Although the generated images can fool human eyes, it is not clear whether they can evade the detection of forensic detectors, which aim to identify the originality and authenticity of images. In this paper, we investigate how forensic detectors perform in differentiating between GAN generated images and real images. We consider two kinds of approaches, one is intrusive and the other is non-intrusive, based on whether the GAN architecture is needed for performing detection. We have conducted extensive experiments on a celebrity face image dataset to evaluate the effectiveness of different approaches. The results and analyses show that the intrusive approach can detect GAN generated images but with a relatively high false alarm rate. The non-intrusive approach with features extracted from a VGG network is very effective for detecting GAN generated images when the training data is sufficient, but it still faces challenge when the training data and testing data are mismatched.

关键词： Gallium nitride Face Detectors Training Training data Generators Histograms

来源：评论

学校读者我要写书评

暂无评论

Weight Learning in Weighted ELM Classification Model Based on Genetic Algorithms

Weight Learning in Weighted ELM Classification Model Based o...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Peng Yao Xi-Zhao Wang Big Data Institute College of Computer Science and Software Engineering Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen Guangdong China

ISBN: (纸本)9781538652152

In cost sensitive classification problems we often suppose to have a known cost matrix in which each element represents the cost of mistakenly classifying an object from one class into another. Weighted least square, which does not equally consider individual classes and therefore assigns a different weight to each class of samples, is a typical approach to dealing with cost sensitive classification problems. Theoretically and experimentally it is confirmed that reasonable class weights will greatly improve classification ability of a learning model. Unfortunately we only know that these weights depend generally on cost matrix but very few methods can be used to specifically determine these weights according to cost matrix. This paper proposes a weighted least square (WLS) model of random weight network and then successfully uses the model in cost sensitive classification. A genetic algorithm to determine weights of different sample classes based on a cost matrix is given. Model analysis and experimental simulations are conducted. Considering the total misclassification cost as the evaluation index, a comparative study shows that our WLS model is far superior to the existing cost sensitive ELM and cost sensitive naive Bayes models.

关键词： Training Genetic algorithms Data models Analytical models Indexes Support vector machines Decision trees

来源：评论

学校读者我要写书评

暂无评论

Erratum: EFNet: evidence fusion network for tumor segmentation from PET-CT volumes (2021 Phys. Med. Biol.66 205005)

引用

Physics in medicine and biology 2021年第24期66卷

作者： Zhaoshuo Diao Huiyan Jiang Xian-Hua Han Yu-Dong Yao Tianyu Shi Software College Northeastern University Shenyang 110819 People's Republic of China. Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang 110819 People's Republic of China. Graduate School of Sciences and Technology for Innovation Yamaguchi University Yamaguchi-shi 7538511 Japan. Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken NJ 07030 United States of America.

来源：评论

学校读者我要写书评

暂无评论

A beam search approach based on action space for the 2D rectangular packing problem 1

引用

9th International Symposium on Intelligence Computation and Applications, ISICA 2017

作者： Yin, Aihua Wang, Lei Hu, Dongping Rao, Hao Deng, Song School of Software and Internet of Things Engineering Jiangxi University of Finance and Economics NanchangJiangxi330023 China College of Computer Science and Technology Wuhan University of Science and Technology WuhanHubei430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System WuhanHubei430081 China

ISBN: (数字)9789811316517

ISBN: (纸本)9789811316500

A beam search algorithm is presented to solve the 2D rectangular packing problem. The basic algorithms work according to 7 rule vectors of heuristic selection rules designed to select a corner-sticking action. Furthermore, the trade-off scheme of breadth first search (BFS) and the depth first search (DFS) increases the algorithm’s effectiveness and efficiency. The improved version of the algorithm adopts a rough phase to get a height for the stripe and a refine phase to obtain better solution for the problem. Computational experiments run on two sets of well-known benchmark instances and the computational results show that the algorithm outperforms the current best algorithms. Especially, for two benchmark instances ZDF6 and ZDF7, our algorithm finds the best packing configurations so far. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Semi-supervised classification method of SAR images using spectral clustering in contourlet domain

引用

Journal of Physics: Conference Series 2020年第4期1486卷

作者： Kaiwen Jiang Degan Zhang Haixia Xu Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education 300384 China Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology Tianjin China School of Electronic and Information Engineering Tianjin Vocational Institute Tianjin 300410 China

A new based on Semi-supervised classification theory for SAR images in contourlet domain is proposed, in this paper. Attempting to get better and faster performance, the PSO algorithm (Particle swarm optimization algorithm) and contourlet domain is proposed to instead of traditional k-means algorithm. PSO is used to find the global optimum by performing a global search in the whole solution space. And then, contourlet is applied in front of construct the similarity matrix to extract more effective eigenvalues. In section five, the proposed algorithm got better classification results than the traditional k-means algorithm which is proved by experimental results show that in terms of running time, classification accuracy and Kappa coefficient.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Layered Co-evolution Based Rough Feature Selection Using Adaptive Neighborhood Radius Hierarchy and Its Application in 3D-MRI

引用

Chinese Journal of Electronics 2017年第6期26卷 1168-1176页

作者： DING Weiping GUAN Zhijin WANG Jiehua TIAN Di School of Computer Science and Technology Nantong University State Key Laboratory for Novel Software Technology Nanjing University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing University of Science and Technology

As the conventional feature selection algorithms are prone to the poor running efficiency in largescale datasets with interacting features, this paper aims at proposing a novel rough feature selection algorithm whose innovation centers on the layered co-evolutionary strategy with neighborhood radius hierarchy. This hierarchy can adapt the rough feature scales among different layers as well as produce the reasonable decompositions through exploiting any correlation and interdependency among feature subsets. Both neighborhood interaction within layer and neighborhood cascade between layers are adopted to implement the interactive optimization of neighborhood radius matrix, so that both the optimal rough feature selection subsets and their global optimal set are obtained efficiently. Our experimental results substantiate the proposed algorithm can achieve better effectiveness, accuracy and applicability than some traditional feature selection algorithms.

关键词： Layered co-evolution Rough feature se lection Adaptive neighborhood radius hierarchy Longitudinal cortical surface labeling

来源：评论

学校读者我要写书评

暂无评论

A Multi-Criteria Band Selection Method of Hyperspectral Images

引用

Journal of Physics: Conference Series 2020年第1期1651卷

作者： Zhonghua Wang Yulin Zhao Bangsheng He Hao Wang Jiangxi Provincial Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Nanchang Jiangxi 330099 China Pioneer Software Co. Ltd Nanchang Jiangxi 330029 China School of Information and Engineering Nanchang Hangkong University Nanchang Jiangxi 330063 China

Hyperspectral remote sensing images are characterized by many bands and large amounts of datum, which require the dimensionality reduction, but band selection is one of the basic methods for dimensionality reduction of hyperspectral datum. For this reason, this paper proposes a multi-criteria band selection method. Firstly, the intrinsic dimensionality of hyperspectral image is calculated by virtual dimension, then the subspace is divided according to the band correlation criterion; and secondly, the information criterion is adopted to select the high-quality exponential bands in each subspace; and finally, the most suitable bands in each subspace are selected by class separability criterion to form the optimal band subset. Various experiments show that, compared with the optimum index factor and adaptive band selection methods, the proposed method has better performance in the measurement of information volume and information redundancy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Modeling multi-turn conversation with deep utterance aggregation 27

Modeling multi-turn conversation with deep utterance aggrega...

引用

27th International Conference on Computational Linguistics, COLING 2018

作者： Zhang, Zhuosheng Li, Jiangtong Zhu, Pengfei Zhao, Hai Liu, Gongshen Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai200240 China College of Zhiyuan Shanghai Jiao Tong University China School of Cyber Security Shanghai Jiao Tong University China School of Computer Science and Software Engineering East China Normal University China

ISBN: (纸本)9781948087506

Multi-turn conversation understanding is a major challenge for building intelligent dialogue systems. This work focuses on retrieval-based response matching for multi-turn conversation whose related work simply concatenates the conversation utterances, ignoring the interactions among previous utterances for context modeling. In this paper, we formulate previous utterances into context using a proposed deep utterance aggregation model to form a fine-grained context representation. In detail, a self-matching attention is first introduced to route the vital information in each utterance. Then the model matches a response with each refined utterance and the final matching score is obtained after attentive turns aggregation. Experimental results show our model outperforms the state-of-the-art methods on three multi-turn conversation benchmarks, including a newly introduced e-commerce dialogue corpus. © 2018 COLING 2018 - 27th International Conference on Computational Linguistics, Proceedings. All rights reserved.

关键词： Speech processing

来源：评论

学校读者我要写书评

暂无评论

Simultaneous spectral-spatial feature selection and extraction for hyperspectral images

arXiv

引用

arXiv 2019年

作者： Zhang, Lefei Zhang, Qian Du, Bo Huang, Xin Tang, Yuan Yan Tao, Dacheng State Key Laboratory of Software Engineering School of Computer Wuhan University Wuhan430072 China Beijing Samsung Telecom R&D Center Beijing100028 China School of Remote Sensing and Information Engineering Wuhan University Wuhan430072 China Department of Computer and Information Science University of Macau Macau999078 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia

In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation hasn't efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address the these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectralspatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient. Copyright © 2019, The Authors. All rights reserved.

关键词： 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：