咨询与建议

限定检索结果

文献类型

  • 141 篇 期刊文献
  • 75 篇 会议

馆藏范围

  • 216 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 142 篇 工学
    • 103 篇 计算机科学与技术...
    • 87 篇 软件工程
    • 25 篇 生物工程
    • 23 篇 信息与通信工程
    • 23 篇 生物医学工程(可授...
    • 20 篇 控制科学与工程
    • 16 篇 光学工程
    • 15 篇 电气工程
    • 11 篇 电子科学与技术(可...
    • 7 篇 机械工程
    • 7 篇 化学工程与技术
    • 6 篇 建筑学
    • 6 篇 土木工程
    • 5 篇 仪器科学与技术
    • 5 篇 交通运输工程
  • 93 篇 理学
    • 53 篇 数学
    • 31 篇 生物学
    • 30 篇 统计学(可授理学、...
    • 29 篇 物理学
    • 13 篇 系统科学
    • 6 篇 化学
    • 6 篇 地球物理学
  • 33 篇 管理学
    • 22 篇 图书情报与档案管...
    • 15 篇 管理科学与工程(可...
    • 7 篇 工商管理
  • 14 篇 医学
    • 13 篇 临床医学
    • 12 篇 基础医学(可授医学...
    • 7 篇 公共卫生与预防医...
    • 6 篇 药学(可授医学、理...
  • 4 篇 经济学
    • 4 篇 应用经济学
  • 4 篇 农学
  • 3 篇 教育学
  • 2 篇 法学
  • 1 篇 哲学
  • 1 篇 文学
  • 1 篇 艺术学

主题

  • 10 篇 machine learning
  • 9 篇 reinforcement le...
  • 8 篇 accuracy
  • 7 篇 deep learning
  • 5 篇 contrastive lear...
  • 5 篇 predictive model...
  • 4 篇 cognition
  • 4 篇 image segmentati...
  • 4 篇 data models
  • 4 篇 training
  • 3 篇 object detection
  • 3 篇 transformers
  • 3 篇 neural networks
  • 3 篇 data engineering
  • 3 篇 semantics
  • 3 篇 benchmarking
  • 3 篇 stochastic syste...
  • 3 篇 biomedical imagi...
  • 3 篇 synchronization
  • 3 篇 robustness

机构

  • 24 篇 center for data ...
  • 7 篇 center for machi...
  • 7 篇 college of compu...
  • 7 篇 peng cheng labor...
  • 7 篇 national key lab...
  • 6 篇 center for data ...
  • 6 篇 key laboratory o...
  • 6 篇 school of data a...
  • 6 篇 the state key la...
  • 6 篇 dortmund data sc...
  • 5 篇 guangdong key la...
  • 5 篇 software college...
  • 5 篇 yizhun medical a...
  • 5 篇 tu dortmund univ...
  • 5 篇 school of mathem...
  • 5 篇 school of comput...
  • 5 篇 key laboratory o...
  • 4 篇 collaborative in...
  • 4 篇 informatics inst...
  • 4 篇 school of mathem...

作者

  • 17 篇 wang liwei
  • 7 篇 wang dong
  • 7 篇 triantafyllopoul...
  • 7 篇 schuller björn w...
  • 6 篇 zhao ziwei
  • 5 篇 zheng wei-shi
  • 5 篇 bakas spyridon
  • 5 篇 zhong han
  • 5 篇 liwei wang
  • 4 篇 yin jianwei
  • 4 篇 müller arthur
  • 4 篇 li hongwei bran
  • 4 篇 tsangko iosif
  • 4 篇 yu hong-xing
  • 4 篇 andreas triantaf...
  • 4 篇 linguraru marius...
  • 4 篇 di he
  • 4 篇 munteanu alexand...
  • 4 篇 müller emmanuel
  • 4 篇 he di

语言

  • 188 篇 英文
  • 27 篇 其他
检索条件"机构=Center for Machine Intelligence and Data Science"
216 条 记 录,以下是21-30 订阅
排序:
Differentiable and Scalable Generative Adversarial Models for data Imputation (Extended Abstract)  40
Differentiable and Scalable Generative Adversarial Models fo...
收藏 引用
40th IEEE International Conference on data Engineering, ICDE 2024
作者: Wu, Yangyang Wang, Jun Miao, Xiaoye Wang, Wenjia Yin, Jianwei Software College Zhejiang University Ningbo China Academy of Interdisciplinary Studies The Hong Kong University of Science and Technology Hong Kong Hong Kong Center for Data Science Zhejiang University Hangzhou China The State Key Lab of Brain-Machine Intelligence Zhejiang University Hangzhou China Guangzhou China College of Computer Science Zhejiang University Hangzhou China
The dramatically increasing volume of incomplete data makes the imputation models computationally infeasible in many real-life applications. In this paper, we propose an effective scalable imputation system named SCIS... 详细信息
来源: 评论
Thai Conversational Chatbot Classification Using BiLSTM and data Augmentation  1st
Thai Conversational Chatbot Classification Using BiLSTM and ...
收藏 引用
1st International Conference on data science and Artificial intelligence, DSAI 2023
作者: Lhasiw, Nunthawat Tanantong, Tanatorn Sanglerdsinlapachai, Nuttapong Thammasat Research Unit in Data Innovation and Artificial Intelligence Department of Computer Science Faculty of Science and Technology Thammasat University Pathum Thani Thailand Strategic Analytics Networks with Machine Learning and AI Research Team National Electronics and Computer Technology Center Pathum Thani Thailand
Chatbot platforms, e.g., Facebook and Line, have revolutionized human interaction in the digital age. In order to develop an automatic chatbot classification, there are several challenges especially for Thai chat mess... 详细信息
来源: 评论
On the Effectiveness of Heterogeneous Ensemble Methods for Re-identification
arXiv
收藏 引用
arXiv 2024年
作者: Klüttermann, Simon Rutinowski, Jérôme Nguyen, Anh Grimme, Britta Roidl, Moritz Müller, Emmanuel TU Dortmund University Dortmund Germany Lamarr Institute for Machine Learning and Artificial Intelligence Germany Research Center Trustworthy Data Science and Security Germany
In this contribution, we introduce a novel ensemble method for the re-identification of industrial entities, using images of chipwood pallets and galvanized metal plates as dataset examples. Our algorithms replace com... 详细信息
来源: 评论
Smaller Batches, Bigger Gains? Investigating the Impact of Batch Sizes on Reinforcement Learning Based Real-World Production Scheduling
Smaller Batches, Bigger Gains? Investigating the Impact of B...
收藏 引用
International Conference on Emerging Technologies and Factory Automation (ETFA)
作者: Arthur Müller Felix Grumbach Matthia Sabatelli Department of Machine Intelligence Fraunhofer IOSB-INA Lemgo Germany Center for Applied Data Science Hochschule Bielefeld Gütersloh Germany Department of Artificial Intelligence University of Groningen Groningen The Netherlands
Production scheduling is an essential task in manufacturing, with Reinforcement Learning (RL) emerging as a key solution. In a previous work, RL was utilized to solve an extended permutation flow shop scheduling probl... 详细信息
来源: 评论
FEDLWS: FEDERATED LEARNING WITH ADAPTIVE LAYER-WISE WEIGHT SHRINKING
arXiv
收藏 引用
arXiv 2025年
作者: Shi, Changlong Li, Jinmeng Zhao, He Guo, Dandan Chang, Yi School of Artificial Intelligence Jilin University China CSIRO’s Data61 Australia International Center of Future Science Jilin University China Engineering Research Center of Knowledge-Driven Human-Machine Intelligence MOE China
In Federated Learning (FL), weighted aggregation of local models is conducted to generate a new global model, and the aggregation weights are typically normalized to 1. A recent study identifies the global weight shri... 详细信息
来源: 评论
Towards Development of Automated Knowledge Maps and databases for Materials Engineering using Large Language Models
arXiv
收藏 引用
arXiv 2024年
作者: Prasad, Deepak Pimpude, Mayur Alankar, Alankar Artificial Intelligence and Data Science Vivekanand Education Society Institute of Technology Mumbai India Department of Mechanical Engineering Indian Institute of Technology Bombay Mumbai400076 India Center for Machine Intelligence and Data Science Indian Institute of Technology Bombay Mumbai400076 India
In this work a Large Language Model (LLM) based workflow is presented that utilizes OpenAI ChatGPT model GPT-3.5-turbo-1106 and Google Gemini Pro model to create summary of text, data and images from research articles... 详细信息
来源: 评论
CBAM-SAUNet: A novel attention U-Net for effective segmentation of corner cases  46
CBAM-SAUNet: A novel attention U-Net for effective segmentat...
收藏 引用
46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024
作者: Rajamani, Srividya Tirunellai Rajamani, Kumar Angeline, J. Karthika, R. Schuller, Björn W. Embedded Intelligence for Health Care & Wellbeing University of Augsburg Germany Department of Artificial Intelligence Marwadi University Gujarat Rajkot India Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India Germany Munich Data Science Institute Germany Munich Center for Machine Learning GLAM-the Group on Language Audio & Music Imperial College London London United Kingdom
U-Net has been demonstrated to be effective for the task of medical image segmentation. Additionally, integrating attention mechanism into U-Net has been shown to yield significant benefits. The Shape Attentive U-Net ... 详细信息
来源: 评论
Can Language Models Serve as Temporal Knowledge Bases?
Can Language Models Serve as Temporal Knowledge Bases?
收藏 引用
2022 Findings of the Association for Computational Linguistics: EMNLP 2022
作者: Zhao, Ruilin Zhao, Feng Xu, Guandong Zhang, Sixiao Jin, Hai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China Data Science and Machine Intelligence Lab University of Technology Sydney Sydney Australia
Recent progress regarding the use of language models (LMs) as knowledge bases (KBs) has shown that language models can act as structured knowledge bases for storing relational facts. However, most existing works only ... 详细信息
来源: 评论
Reinforcement Learning as an Improvement Heuristic for Real-World Production Scheduling
Reinforcement Learning as an Improvement Heuristic for Real-...
收藏 引用
International Conference on machine Learning and Applications (ICMLA)
作者: Arthur Müller Lukas Vollenkemper Department of Machine Intelligence Fraunhofer IOSB-INA Lemgo Germany Center for Applied Data Science Bielefeld University of Applied Sciences and Arts Gütersloh Germany
The integration of Reinforcement Learning (RL) with heuristic methods is an emerging trend for solving optimization problems, which leverages RL's ability to learn from the data generated during the search process... 详细信息
来源: 评论
DFingerNet: Noise-Adaptive Speech Enhancement for Hearing Aids
DFingerNet: Noise-Adaptive Speech Enhancement for Hearing Ai...
收藏 引用
2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025
作者: Tsangko, Iosif Triantafyllopoulos, Andreas Müller, Michael Schröter, Hendrik Schuller, Björn W. EIHW - Embedded Intelligence for Health Care and Wellbeing University of Augsburg Germany Technical University of Munich Germany MCML - Munich Center for Machine Learning Munich Germany WS Audiology Research and Development Erlangen Germany GLAM - Group on Language Audio & Music Imperial College London United Kingdom MDSI - Munich Data Science Institute Munich Germany
The DeepFilterNet (DFN) architecture was recently proposed as a deep learning model suited for hearing aid devices. Despite its competitive performance on numerous benchmarks, it still follows a 'one-size-fits-all... 详细信息
来源: 评论