检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

998 篇 会议
66 篇 期刊文献
34 册 图书

馆藏范围

1,098 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

510 篇 工学
- 389 篇 计算机科学与技术...
- 239 篇 软件工程
- 135 篇 生物工程
- 81 篇 生物医学工程（可授...
- 43 篇 信息与通信工程
- 34 篇 电气工程
- 32 篇 控制科学与工程
- 30 篇 光学工程
- 29 篇 化学工程与技术
- 15 篇 机械工程
- 15 篇 电子科学与技术（可...
- 12 篇 仪器科学与技术
- 9 篇 交通运输工程
375 篇 理学
- 204 篇 数学
- 185 篇 生物学
- 127 篇 统计学（可授理学、...
- 45 篇 系统科学
- 42 篇 物理学
- 30 篇 化学
96 篇 管理学
- 59 篇 图书情报与档案管...
- 36 篇 管理科学与工程(可...
- 17 篇 工商管理
81 篇 医学
- 70 篇 基础医学(可授医学...
- 17 篇 临床医学
- 14 篇 药学(可授医学、理...
- 7 篇 公共卫生与预防医...
25 篇 农学
- 22 篇 作物学
9 篇 法学
- 9 篇 社会学
7 篇 教育学
- 7 篇 教育学
7 篇 文学
- 7 篇 新闻传播学
5 篇 经济学
3 篇 军事学

主题

195 篇 bioinformatics
112 篇 predictive model...
87 篇 biological syste...
73 篇 proteins
70 篇 prediction algor...
67 篇 data models
66 篇 genomics
52 篇 hidden markov mo...
51 篇 computational mo...
44 篇 algorithms
44 篇 clustering algor...
44 篇 accuracy
43 篇 support vector m...
37 篇 gene expression
36 篇 training
35 篇 machine learning
33 篇 feature extracti...
33 篇 classification a...
32 篇 machine learning...
30 篇 diseases

机构

5 篇 college of compu...
5 篇 higher technical...
5 篇 nova university ...
4 篇 department of co...
4 篇 school of comput...
4 篇 florida atlantic...
3 篇 harbin inst tech...
3 篇 department of el...
3 篇 bioinformatics a...
3 篇 school of comput...
3 篇 formal methods a...
2 篇 beijing key labo...
2 篇 departament d’en...
2 篇 national institu...
2 篇 division of biom...
2 篇 institute for in...
2 篇 ist/inesc-id tec...
2 篇 univ saskatchewa...
2 篇 department of el...
2 篇 department of co...

作者

6 篇 ignacio rojas
6 篇 gonzalo joya
4 篇 joan cabestany
4 篇 pardamean bens
4 篇 fang-xiang wu
4 篇 hugo gamboa
4 篇 lei deng
4 篇 yang li
4 篇 ana fred
3 篇 lei wang
3 篇 van de pol jaco
3 篇 maozu guo
3 篇 megherbi dalila ...
3 篇 shaoliang peng
3 篇 jianxin wang
3 篇 van der aalst wi...
3 篇 chun-hou zheng
3 篇 rocha miguel
3 篇 fa zhang
3 篇 saghir helal

语言

1,091 篇 英文
6 篇 其他
1 篇 中文

检索条件"任意字段=International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2013"

共 1098 条记录，以下是61-70 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

FNOReg: Resolution-Robust Medical Image Registration Method Based on Fourier Neural Operator 27th

FNOReg: Resolution-Robust Medical Image Registration Method ...

引用

27th international conference on Pattern Recognition, ICPR 2024

作者： Drozdov, Nikita A. Sorokin, Dmitry V. Laboratory of Mathematical Methods of Image Processing Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Moscow Russia

ISBN: (纸本)9783031782008

Medical image registration plays a crucial role in diagnosis, treatment planning, and anatomical studies. Classical methods, relying on iterative optimization algorithms, are complex and computationally intensive. Recent advances in deep learning, particularly with convolutional neural networks (CNNs) like VoxelMorph, have shown promise. However, they often yield non-smooth deformation fields and require inference at the same image resolution as the training data. To overcome these challenges, we introduce FNOReg, a novel model based on Fourier Neural Operators (FNOs), which can be trained on reduced-resolution images without quality loss and produces smoother deformation fields. We evaluated FNOReg on 2D and 3D datasets, demonstrating comparable quality to popular models like VoxelMorph, Fourier-Net, and TransMorph when trained at the same resolution. However, these models exhibit significant quality decreases of up to 24.9% for 2D and 24.6% for 3D data, when trained at halved resolutions. In contrast, FNOReg demonstrates only marginal quality decreases of up to 0.8% for 2D and 2.7% for 3D data. This flexibility is essential for efficiently handling large image resolutions, particularly in 3D imaging. Moreover, FNOReg produces smoother deformation fields. The code is available at https://***/anac0der/fnoreg. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

20th international Colloquium on Theoretical Aspects of Computing, ICTAC 2023

20th International Colloquium on Theoretical Aspects of Comp...

引用

20th international Colloquium on Theoretical Aspects of Computing, ICTAC 2023

ISBN: (纸本)9783031479625

The proceedings contain 25 papers. The special focus in this conference is on Theoretical Aspects of Computing. The topics include: An Autonomous Data Language;formal Language Semantics for Triggered Enable Statecharts with a Run-to-Completion Scheduling;strong Call-by-Value and Multi Types;algorithms for Checking Intersection Non-emptiness of Regular Expressions;realisability of Global models of Interaction;efficient Reactive Synthesis Using Mode Decomposition;a Categorical Approach to Synthetic Chemistry;closure and Decision Properties for Higher-Dimensional Automata;robustness in Metric Spaces over Continuous Quantales and the Hausdorff-Smyth Monad;without Loss of Satisfaction;synchronous Agents, Verification, and Blame—A Deontic View;store Locally, Prove Globally;denotational Semantics for Symbolic Execution;TeSSLa-ROS-Bridge – Runtime Verification of Robotic Systems;simplifying Process Parameters by Unfolding Algebraic Data Types;modular Soundness Checking of Feature Model Evolution Plans;modelling and Verifying Robotic Software that Uses Neural Networks;a Game-Theoretic Approach to Indistinguishability of Winning Objectives as User Privacy;learning Attack Trees by Genetic algorithms;the Landscape of Computing Symmetric n-Variable Functions with 2n Cards;on the Complexity of Reasoning in Kleene Algebra with Commutativity Conditions;towards the Complexity Analysis of Programming Language Proof methods;a Dynamic Temporal Logic for Quality of Service in Choreographic models.

关键词：

来源：评论

学校读者我要写书评

暂无评论

37th international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2024

37th International Conference on Industrial, Engineering and...

引用

37th international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2024

ISBN: (纸本)9789819746767

The proceedings contain 41 papers. The special focus in this conference is on Industrial, Engineering and Other Applications of Applied Intelligent Systems. The topics include: A Sparse Binary Data Clustering Method for Transaction Data;improving Noise Robustness of Automatic Speech Recognition Based on a Parallel Adapter Model with Near-Identity Initialization;reconsidering Stochastic Policy Gradient methods for Traffic Signal Control;Hybrid Additive Manufacturing: A Convergence of Physical, Digital, and Social Realms Driven by Generative AI;towards Eco-Friendly Multi-compartment Transportation: A New Bi-objective Iterated Local Search Framework;simulation Optimization of Operating Room Schedules for Elective Surgeries;learning Causality Under Uncertainty for Egocentric Action Anticipation;time Heals Unfairness: Efficient Dynamic Routing at an Autonomous Society;Parallel Implementation of a Convolutional Neural Network on an MPSoC;deep Residual Networks for Pigmented Skin Lesions Diagnosis;weightless Neural Networks Based on Multi-valued Probabilistic Logic for Node for the Handwritten Digit Classification;formal Verification of Neural Networks: A "Step Zero" Approach for Vehicle Detection;PPG-Based Heart Rate Estimation Using Unsupervised Domain Adaptation;a Novel Multi-task Single-Step Traffic Congestion Forecasting Framework for Large-Scale Road Networks;towards Addressing an Open Problem in Coupled Matrix Tensor Factorization for Satellite Imagery Data Using Human-in-Loop;representation and Generation of Music: Incorporating Composers’ Perspectives into Deep Learning models;evaluation Techniques for Long Short-Term Memory models: Overfitting Analysis and Handling Missing Values;Live Product Line Engineering Using Density-Based Clustering of CAD models;fog-Based Ransomware Detection for Internet of Medical Things Using Lighweight Machine Learning algorithms;verifying Autoencoders for Anomaly Detection in Predictive Maintenance;a Computer Vision Based Approach fo

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Study of Classification Techniques Based on Spike Protein Sequences of MERS-CoV 10

A Study of Classification Techniques Based on Spike Protein ...

引用

10th international conference on Biomedical and bioinformatics Engineering (ICBBE)

作者： Kim, Hayeon Cho, Myeongji Son, Hyeon S. Seoul Natl Univ Lab Computat Biol & Bioinformat Grad Sch Publ Hlth Seoul South Korea Seoul Natl Univ Inst Hlth & Environm Seoul South Korea Seoul Natl Univ Coll Nat Sci Interdisciplinary Grad Program Bioinformat Seoul South Korea

ISBN: (纸本)9798400708343

MERS-CoV, which belongs to the beta-coronaviruses together with SARS-CoV-2, although it has received relatively less attention by the COVID-19 pandemic, there is a sufficient possibility of new MERS-CoV lineages and variants. Previous studies have discussed the possibility of frequent recombination of MERS-CoV. We thus present a highly accurate method for the phylogenetic analysis and classification of MERS-CoV including recombinant sequences. We collected the sequences of S protein from MERS-CoV and divided them into five phylogenetic groups, of which recombinant sequences were divided into seven types. Physicochemical properties of amino acids were then calculated from the S protein sequences, and the results were used for the random forest model, Naive Bayes classification, and k-nearest neighbor method. We also constructed several feature subsets based on the ranked amino acid properties and applied them to the random forest model. In each dataset, the amino acid physicochemical properties were ranked differently. Using this information, classification of MERS-CoV based on machine learning algorithms showed that the random forest model had the best accuracy and area under the curve compared with the k-nearest neighbor and Naive Bayes classification methods. Several feature subsets were constructed using the correlation feature selection algorithm and applied to the random forest model. Overall, the performance of the classifier was improved compared to that when using all features. Coronaviruses including MERS-CoV continue to evolve into new forms through recombination or mutation. We thus present a method to increase the accuracy of their classification using additional information of the viral protein sequence, and confirm that a subunit consisting of optimal prominent features can improve the performance of the classifier by removing the unnecessary characteristic information.

关键词： MERS-CoV machine learning classification

来源：评论

学校读者我要写书评

暂无评论

EEG-based Cross Subject Emotion Recognition based on collaborative learning and dynamic distribution adaptation

EEG-based Cross Subject Emotion Recognition based on collabo...

引用

IEEE international conference on bioinformatics and Biomedicine (BIBM)

作者： Jin Gu Fei Xiong Xinhao Gong School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

EEG-based emotion recognition has advanced rapidly due to its objectivity and reliability, but individual differences present challenges: subject-specific models underperform on new subjects, and general models lack accuracy. While domain adaptation (DA) algorithms reduce distribution differences between source and target EEG domains, single-source methods struggle with knowledge transfer, and multi-source methods neglect source domain differences. To address this, we propose a collaborative learning and dynamic distributed adaptation algorithm (CL-DDA) for EEG emotion recognition. By dividing the model into two sub-networks, collaborative learning improves generalization. Additionally, local subdomain alignment addresses inter-subject emotion differences, while global domain alignment minimizes marginal distribution disparities. Our model achieved 90.08% and 77.55% accuracy on SEED and SEED-IV datasets, respectively, in cross-subject emotion recognition.

关键词： Emotion recognition Adaptation models Accuracy Federated learning Heuristic algorithms Biological system modeling Brain modeling Electroencephalography Reliability Knowledge transfer

来源：评论

学校读者我要写书评

暂无评论

14th international conference on Large-Scale Scientific Computations, LSSC 2023

14th International Conference on Large-Scale Scientific Comp...

引用

14th international conference on Large-Scale Scientific Computations, LSSC 2023

ISBN: (纸本)9783031562075

The proceedings contain 50 papers. The special focus in this conference is on Large-Scale Scientific Computations. The topics include: Numerical Comparison of Block Preconditioners for Poroelasticity;Two-Dimensional Semi-linear Riesz Space Fractional Diffusion Equations in Convex Domains: GLT Spectral Analysis and Multigrid Solvers;continuation Newton methods with Applications to Plasticity;mixed and Nitsche’s Discretizations of Frictional Contact-Mechanics in Fractured Porous Media;Towards Efficient SOT-Assisted STT-MRAM Cell Switching Using Reinforcement Learning;machine Learning algorithms for Parameter Identification for Reactive Flow in Porous Media;randomized Symplectic Model Order Reduction for Hamiltonian Systems;Adaptive Localized Reduced Basis methods for Large Scale PDE-Constrained Optimization;Application of Deep Kernel models for Certified and Adaptive RB-ML-ROM Surrogate Modeling;parametric Analysis of Space-Time Fractional Pennes Bioheat Model Using a Collocation Method Based on Radial Basis Functions and Chebyshev Polynomials;numerical Determination of Source from Point Observation in a Time-Fractional Boundary-Value Problem on Disjoint Intervals;the Wright Function – Numerical Approximation and Hypergeometric Representation;Study of Sparsification Schemes for the FEM Stiffness Matrix of Fractional Diffusion Problems;fractional Diffusion Problems with Reflecting Boundaries;A Mean Field Model for Counter CBRN Threats;a Sufficient Condition for a Discrete-Time Optimal Control Problem;computation of the Unknown Time-Dependent Volatility of American Options from Integral Observations;efficient Solution of Stochastic Galerkin Matrix Equations via Reduced Basis and Tensor Train Approximation;the Tensor-Train Mimetic Finite Difference Method for Three-Dimensional Maxwell’s Wave Propagation Equations;A Functional Tensor Train Library in RUST for Numerical Integration and Resolution of Partial Differential Equations;solving the Mountain Car Problem Using Gene

关键词：

来源：评论

学校读者我要写书评

暂无评论

Biomarkers for ovarian cancer for the accurate detection and classification using computational algorithms and interpreting using explainers

Biomarkers for ovarian cancer for the accurate detection and...

引用

Computational Intelligence for Security, Communication and Sustainable Development (CISCSD), international conference on

作者： Iffath Jahan Ashi Srivastava Ashwini Kodipalli Trupthi Rao Artificial Intelligence and Data Science Global Academy Of Technology Bangalore India

ISBN: (数字)9798350365405

ISBN: (纸本)9798350365412

Ovarian cancer remains a significant challenge in oncology due to its high mortality rates, often attributed to late-stage diagnosis and lack of effective screening methods. Biomarkers are essential for the precise identification and categorization of ovarian cancer, providing the opportunity for early diagnosis and individualized treatment plans. In this work, we examine how computational methods can be used to better diagnose and classify ovarian cancer by utilizing biomarker data. Through a rigorous assessment of the literature and bioinformatics analysis, a panel of biomarkers with promising uses in diagnosis and prognosis is found. Next, we employ numerous machine learning techniques, including as random forests and support vector machines, and deep learning architectures, to develop prediction models that have been trained using proteomic and genomic data. We use explainable AI techniques, such LIME and SHAP, to improve the interpretability of these models by offering clear insights into the decision-making process. The computational algorithms are effective in precisely identifying and categorizing subtypes of ovarian cancer according to biomarker profiles. Additionally, by establishing a correlation between computational predictions and treatment outcomes and patient outcomes, we clarify the clinical significance of these findings. This work highlights the potential of computational approaches to improve ovarian cancer diagnosis, and highlights the significance of interpretable models in enabling clinical translation and decision-making.

关键词： Machine learning algorithms Computational modeling Biological system modeling Decision making Biomarkers Predictive models Prediction algorithms Classification algorithms bioinformatics Ovarian cancer

来源：评论

学校读者我要写书评

暂无评论

LM-ARG: Identification & classification of antibiotic resistance genes leveraging pre-trained protein language models

LM-ARG: Identification & classification of antibiotic resist...

引用

2022 IEEE international conference on bioinformatics and Biomedicine, BIBM 2022

作者： Ahmed, Shafayat Emon, Muhit Islam Moumi, Nazifa Ahmed Zhang, Liqing Virginia Polytechnic Institute and State University Department of Computer Science BlacksburgVA United States

ISBN: (纸本)9781665468190

Antibiotic resistance is a silent pandemic, causing 700 thousand human deaths across the world every year. Antibiotic resistance genes (ARG) are genes conferring resistance for the bacteria carrying them. Predicting ARGs is an important computational task. Traditionally ARGs are predicted using alignment based methods. However, the false negative rate for most of the alignment-based tools is very high. The protein language models (LM) trained on the huge corpus protein sequences capture distant relations among protein sequences. These features can be utilized for the identification and classification of ARGs. We have presented a self-supervised model on the largest available ARG database with the help of a pre-trained language model ProtAlbert. We used the raw protein LM-embeddings from unlabeled data on our ARG classification task and saw it outperform state-of-the-art prediction algorithms. The extracted features from the pretrained language model boosted the supervised model accuracy to a great margin. © 2022 IEEE.

关键词： Proteins

来源：评论

学校读者我要写书评

暂无评论

AutoShape: Automatic Design of Click-Through Rate Prediction models Using Shapley Value 20th

AutoShape: Automatic Design of Click-Through Rate Prediction...

引用

20th Pacific Rim international conference on Artificial Intelligence, PRICAI 2023

作者： Fang, Yunfei Mu, Caihong Liu, Yi Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Collaborative Innovation Center of Quantum Information of Shaanxi Province School of Artificial Intelligence Xidian University Xi’an710071 China School of Electronic Engineering Xidian University Xi’an710071 China

ISBN: (纸本)9789819970216

As a main part of automated machine learning, Neural Architecture Search (NAS) has been employed in exploring effective Click-Through Rate (CTR) prediction models of recommender systems in recent studies. However, these studies update the architecture parameters by different strategies, such as gradient-based methods or evolutionary algorithms, and may suffer from either interference problems or high time-consuming in the search stage. Besides, the blocks in the search space were usually homogeneous, which means they have the same candidate operations to choose. Such design will result in redundancy in the search space, because many structures are inherently invalid and just increase the complexity of searching. To address the above issues, we implement the three-level automatic design of CTR prediction models using NAS via Shapley value, named as AutoShape. For the search space, we divide it into three parts according to the characteristics of the CTR model. Each part comprises distinctive candidate operations and forms a cell as an individual processing level, which improves the stability of the searched models’ effect and reduces the computational complexity. For the search strategy, we leverage Shapley value, a metric derived from cooperative game theory, to estimate the contribution of the operations in each block and the connections between the blocks, which can find effective models and reduce the time cost. Furthermore, experiments on different benchmark datasets show that the structure obtained from the search performs better than several hand-crafted architectures and is more stable than another NAS-based algorithm. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

TotemBioNet Enrichment Methodology: Application to the Qualitative Regulatory Network of the Cell Metabolism 12

<i>TotemBioNet</i> Enrichment Methodology: Application to th...

引用

14th international Joint conference on Biomedical Engineering Systems and Technologies (BIOSTEC) / 12th international conference on bioinformatics models, methods and algorithms (bioinformatics)

作者： Gibart, Laetitia Bernot, Gilles Collavizza, Helene Comet, Jean-Paul Univ Cote Azur I3S Lab UMR CNRS 7271 CS 40121 F-06903 Sophia Antipolis France

ISBN: (纸本)9789897584909

When designing a biological regulatory network, new information or wet experiments can require adding variables or interactions, inside a previously validated model. They can result in complete reconsiderations of established behaviours. Fortunately, formal methods allow for fully automated verification of properties, and TotemBioNet is an efficient software integrating a collection of formal approaches for regulatory networks. It allowed us to develop a multidisciplinary methodology for designing large dynamical models in an incremental way, including non regression proofs (preservation of important biological properties).

关键词： Formal methods Regulatory Networks R. Thomas' Modelling Parameter Identification Model Enrichment

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共110页 << < 3 4 5 6 7 8 9 10 11 12 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：