咨询与建议

限定检索结果

文献类型

  • 22 篇 会议
  • 18 篇 期刊文献

馆藏范围

  • 40 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 26 篇 工学
    • 21 篇 计算机科学与技术...
    • 20 篇 软件工程
    • 10 篇 生物工程
    • 9 篇 信息与通信工程
    • 5 篇 生物医学工程(可授...
    • 3 篇 光学工程
    • 3 篇 仪器科学与技术
    • 3 篇 控制科学与工程
    • 1 篇 力学(可授工学、理...
    • 1 篇 机械工程
    • 1 篇 材料科学与工程(可...
    • 1 篇 建筑学
    • 1 篇 测绘科学与技术
    • 1 篇 环境科学与工程(可...
    • 1 篇 安全科学与工程
  • 17 篇 理学
    • 10 篇 生物学
    • 7 篇 数学
    • 4 篇 物理学
    • 2 篇 统计学(可授理学、...
    • 1 篇 系统科学
  • 9 篇 管理学
    • 7 篇 图书情报与档案管...
    • 4 篇 管理科学与工程(可...
    • 1 篇 工商管理
  • 3 篇 法学
    • 3 篇 社会学
  • 2 篇 医学
    • 2 篇 基础医学(可授医学...
    • 2 篇 临床医学
    • 2 篇 药学(可授医学、理...
  • 1 篇 教育学
    • 1 篇 教育学
  • 1 篇 农学
    • 1 篇 农业资源与环境

主题

  • 4 篇 training
  • 3 篇 deep neural netw...
  • 2 篇 support vector m...
  • 2 篇 human computer i...
  • 2 篇 anomaly detectio...
  • 2 篇 mapreduce
  • 2 篇 databases
  • 2 篇 machine learning
  • 1 篇 knowledge based ...
  • 1 篇 neurons
  • 1 篇 oceanic chloroph...
  • 1 篇 deep learning
  • 1 篇 magnetic resonan...
  • 1 篇 sensitivity anal...
  • 1 篇 substrates
  • 1 篇 safety
  • 1 篇 sensitivity
  • 1 篇 prevention and m...
  • 1 篇 image segmentati...
  • 1 篇 kernel methods

机构

  • 4 篇 centre for visio...
  • 3 篇 big data institu...
  • 3 篇 université pierr...
  • 3 篇 key lab. of mach...
  • 3 篇 bio-imaging sign...
  • 2 篇 argedor informat...
  • 2 篇 college of mathe...
  • 2 篇 key laboratory o...
  • 2 篇 machine learning...
  • 2 篇 institute of sig...
  • 2 篇 school of comput...
  • 2 篇 information tech...
  • 2 篇 south australian...
  • 2 篇 the shenzhen key...
  • 2 篇 the college of m...
  • 2 篇 palermo
  • 2 篇 visual geometry ...
  • 2 篇 graduate univers...
  • 2 篇 phonetics and ph...
  • 2 篇 signal processin...

作者

  • 5 篇 wang ran
  • 4 篇 adda-decker m.
  • 4 篇 roussel p.
  • 4 篇 denby b.
  • 4 篇 buchman l.
  • 4 篇 chawah p.
  • 4 篇 carneiro gustavo
  • 4 篇 xu k.
  • 4 篇 al kork s.k.
  • 3 篇 pourpanah farhad
  • 3 篇 chen sihong
  • 3 篇 he qing
  • 3 篇 wahab abdul
  • 3 篇 shen haojing
  • 3 篇 li ning
  • 3 篇 stone m.
  • 3 篇 khan shujaat
  • 2 篇 uʇurca d.
  • 2 篇 verjans johan w.
  • 2 篇 dreyfus g.

语言

  • 40 篇 英文
检索条件"机构=Signal Processing and Machine Learning Lab."
40 条 记 录,以下是1-10 订阅
排序:
On dynamic weighting of data in clustering with K-alpha means
On dynamic weighting of data in clustering with K-alpha mean...
收藏 引用
2010 20th International Conference on Pattern Recognition, ICPR 2010
作者: Chen, Si-Bao Wang, Hai-Xian Luo, Bin Key Lab. of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui 230039 China Key Lab. of Child Development and Learning Science Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China
Although many methods of refining initialization have appeared, the sensitivity of K-Means to initial centers is still an obstacle in applications. In this paper, we investigate a new class of clustering algorithm, K-... 详细信息
来源: 评论
A Neuro-Symbolic Approach for Marine Vessels Power Prediction Under Distribution Shifts
A Neuro-Symbolic Approach for Marine Vessels Power Predictio...
收藏 引用
2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology, JEEIT 2023
作者: Hammoudeh, Ahmad Ghannam, Ibrahim Mubarak, Hamza Jean, Emmanuael Vandenbulcke, Virginie Dupont, Stephane MAiA Lab ISlA Lab Umons Trail Belgium RWTH Aachen University Electrical Engineering Germany Griffith University Engineering and Built Environment Australia Machine Learning & Signal Processing Multitel Trail Belgium Umons Isia Lab Belgium Umons Maia Lab Belgium
This paper proposes a neuro-symbolic approach to predict the power of marine cargo vessels. The neuro-symbolic approach combines two parts. The first is a neural networks part, and the second is a symbolic part that r... 详细信息
来源: 评论
On the Robustness of Out-of-Distribution Detection Methods for Camera-based Systems  58
On the Robustness of Out-of-Distribution Detection Methods f...
收藏 引用
58th Asilomar Conference on signals, Systems and Computers, ACSSC 2024
作者: Huber, Christian Lehner, Bernhard Hofmann, Claus Moser, Bernhard Feger, Reinhard Silicon Austria Labs GmbH Jku Lit Sal eSPML Lab Austria Johannes Kepler University Linz Jku Lit Sal eSPML Lab Austria Institute for Machine Learning Austria Institute of Signal Processing China Institute for Communications Engineering and RF-Systems China
Out-of-distribution (OOD) detection refers to recognizing instances that lie outside the scope of what a machine learning model has been exposed to during training. In safetycritical domains like autonomous driving, O... 详细信息
来源: 评论
Revealing Emotional Clusters in Speaker Embeddings: A Contrastive learning Strategy for Speech Emotion Recognition
Revealing Emotional Clusters in Speaker Embeddings: A Contra...
收藏 引用
International Conference on Acoustics, Speech, and signal processing (ICASSP)
作者: Ismail Rasim Ulgen Zongyang Du Carlos Busso Berrak Sisman Speech & Machine Learning (SML) Lab The University of Texas at Dallas USA Multimodal Signal Processing (MSP) Lab The University of Texas at Dallas USA
Speaker embeddings carry valuable emotion-related information, which makes them a promising resource for enhancing speech emotion recognition (SER), especially with limited lab.led data. Traditionally, it has been ass...
来源: 评论
Independent vector analysis for SSVEP signal enhancement
Independent vector analysis for SSVEP signal enhancement
收藏 引用
Annual Conference on Information Sciences and Systems (CISS)
作者: Darren K. Emge François-Benoît Vialatte Gérard Dreyfus Tülay Adalı Department of CSEE University of Maryland Baltimore County MD ESPCI ParisTech. SIGnal processing and MAchine learning (SIGMA) lab France
Steady state visual evoked potentials (SSVEP) have been identified as a highly viable solution for brain computer interface (BCI) systems. The SSVEP is observed in the scalp-based recordings of electroencephalogram (E... 详细信息
来源: 评论
SENSITIVITY ANALYSIS OF GAUSSIAN PROCESSES FOR OCEANIC CHLOROPHYLL PREDICTION
SENSITIVITY ANALYSIS OF GAUSSIAN PROCESSES FOR OCEANIC CHLOR...
收藏 引用
IEEE International Geoscience and Remote Sensing Symposium
作者: Katalin Blix Gustau Camps-Valls Robert Jenssen Machine Learning @ UiT Lab University of Tromso (UiT) - The Arctic University of Norway Image and Signal Processing Group - Universitat de Valencia
Gaussian Process Regression (GPR) for machine learning has lately been successfully introduced for chlorophyll content mapping from remotely sensed data. The method provides a fast, stable and accurate prediction of b... 详细信息
来源: 评论
One network to solve all ROIs: Deep learning CT for any ROI using differentiated backprojection
arXiv
收藏 引用
arXiv 2018年
作者: Han, Yoseob Ye, Jong Chul BISPL - Bio Imaging Signal Processing and Learning lab. Dept. of Bio and Brain Engineering KAIST Daejeon Korea Republic of
Purpose: Computed tomography for the reconstruction of region of interest (ROI) has advantages in reducing the X-ray dose and the use of a small detector. However, standard analytic reconstruction methods such as filt... 详细信息
来源: 评论
PPLSA: Parallel probabilistic latent semantic analysis based on MapReduce
PPLSA: Parallel probabilistic latent semantic analysis based...
收藏 引用
7th IFIP International Conference on Intelligent Information processing, IIP 2012
作者: Li, Ning Zhuang, Fuzhen He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate University Chinese Academy of Sciences Beijing China Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding China
PLSA(Probabilistic Latent Semantic Analysis) is a popular topic modeling technique for exploring document collections. Due to the increasing prevalence of large datasets, there is a need to improve the scalab.lity of ... 详细信息
来源: 评论
A multi-sensor helmet to capture rare singing, an intangible cultural heritage study  10
A multi-sensor helmet to capture rare singing, an intangible...
收藏 引用
10th International Seminar on Speech Production, ISSP 2014
作者: Al Kork, S.K. Jaumard-Hakoun, A. Adda-Decker, M. Amelot, A. Buchman, L. Chawah, P. Dreyfus, G. Fux, T. Pillot-Loiseau, C. Roussel, P. Stone, M. Xu, K. Denby, B. Université Pierre Marie Curie Paris France Signal Processing and Machine Learning Lab ESPCI Paris-Tech Paris France Phonetics and Phonology Laboratory LPP-CNRS UMR7018 University Paris3 Sorbonne Nouvelle France Vocal Tract Visualization Lab University of Maryland Dental School Baltimore United States
A portable helmet based system has been developed to capture motor behavior during singing and other oral-motor functions in a non-lab.ratory experimental environment. The system, based on vocal tract sensing methods ... 详细信息
来源: 评论
Toward big data in QSAR/QSPR
Toward big data in QSAR/QSPR
收藏 引用
IEEE Workshop on machine learning for signal processing
作者: A. Duprat J.L. Ploix F. Dioury G. Dreyfus ESPCI ParisTech SIGnal processing and MAchine learning (SIGMA) lab Paris France Cnam Equipe Chimie Moléculaire Laboratoire CMGPCM Paris France
We investigate a prospective path to processing “big data” in the field of computer-aided drug design, motivated by the expected increase of the size of availab.e databases. We argue that graph machines, which exemp... 详细信息
来源: 评论