咨询与建议

限定检索结果

文献类型

  • 113 篇 会议
  • 25 篇 期刊文献

馆藏范围

  • 138 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 92 篇 工学
    • 75 篇 计算机科学与技术...
    • 58 篇 软件工程
    • 39 篇 信息与通信工程
    • 17 篇 动力工程及工程热...
    • 12 篇 电子科学与技术(可...
    • 8 篇 仪器科学与技术
    • 7 篇 控制科学与工程
    • 6 篇 电气工程
    • 4 篇 机械工程
    • 4 篇 光学工程
    • 4 篇 化学工程与技术
    • 4 篇 生物工程
    • 3 篇 农业工程
    • 3 篇 生物医学工程(可授...
    • 2 篇 建筑学
    • 1 篇 力学(可授工学、理...
    • 1 篇 材料科学与工程(可...
    • 1 篇 土木工程
  • 42 篇 理学
    • 28 篇 数学
    • 6 篇 统计学(可授理学、...
    • 5 篇 化学
    • 5 篇 生物学
    • 4 篇 物理学
    • 4 篇 系统科学
  • 27 篇 管理学
    • 14 篇 管理科学与工程(可...
    • 12 篇 图书情报与档案管...
    • 4 篇 工商管理
  • 8 篇 法学
    • 8 篇 社会学
  • 4 篇 农学
    • 4 篇 作物学
  • 1 篇 经济学
    • 1 篇 应用经济学
  • 1 篇 医学

主题

  • 9 篇 wireless sensor ...
  • 8 篇 sensor nodes
  • 8 篇 graphics process...
  • 7 篇 parallel algorit...
  • 7 篇 algorithm design...
  • 6 篇 collaborative fi...
  • 6 篇 feature extracti...
  • 6 篇 instruction sets
  • 6 篇 adaptation model...
  • 5 篇 semantic segment...
  • 5 篇 deep learning
  • 5 篇 throughput
  • 5 篇 information scie...
  • 5 篇 training
  • 4 篇 transformers
  • 4 篇 recommender syst...
  • 4 篇 target tracking
  • 4 篇 data mining
  • 4 篇 control engineer...
  • 4 篇 social networkin...

机构

  • 66 篇 key laboratory o...
  • 59 篇 school of comput...
  • 26 篇 college of compu...
  • 11 篇 key laboratory o...
  • 7 篇 key laboratory o...
  • 7 篇 key laboratory o...
  • 6 篇 school of comput...
  • 6 篇 school of inform...
  • 5 篇 jiaxiang industr...
  • 4 篇 heilongjiang uni...
  • 3 篇 key laboratory o...
  • 3 篇 heilongjiang uni...
  • 3 篇 department of co...
  • 2 篇 shandong artific...
  • 2 篇 beijing institut...
  • 2 篇 jiaxiang industr...
  • 2 篇 heilongjiang key...
  • 2 篇 college of compu...
  • 2 篇 college of compu...
  • 2 篇 harbin research ...

作者

  • 24 篇 li jinbao
  • 18 篇 jun lu
  • 18 篇 lu jun
  • 18 篇 guo longjiang
  • 14 篇 yan yang
  • 14 篇 yang yan
  • 13 篇 jinbao li
  • 10 篇 ren meirui
  • 9 篇 longjiang guo
  • 9 篇 li jin-bao
  • 7 篇 zhu jinghua
  • 6 篇 zhang desheng
  • 6 篇 zhu jing-hua
  • 6 篇 guo long-jiang
  • 6 篇 zhong yingli
  • 6 篇 meirui ren
  • 5 篇 jun li
  • 5 篇 ruiqing jing
  • 4 篇 nan wang
  • 4 篇 jinghua zhu

语言

  • 118 篇 英文
  • 20 篇 中文
检索条件"机构=Heilongjiang Province Key Laboratory for Database and Parallel Computing"
138 条 记 录,以下是21-30 订阅
排序:
Sensitivity loss training based implicit feedback  27
Sensitivity loss training based implicit feedback
收藏 引用
27th IEEE International Conference on parallel and Distributed Systems, ICPADS 2021
作者: Li, Kun Wang, Nan Liu, Xinyu School of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China
In recommender systems, due to the lack of explicit feedback features, datasets with implicit feedback are always accustomed to train all samples without separating them during model training, without considering the ... 详细信息
来源: 评论
FasterBERT with Double Loss Function Based on Batch Data Preprocessing  2
FasterBERT with Double Loss Function Based on Batch Data Pre...
收藏 引用
2nd International Conference on Electronics, Communications and Information Technology, CECIT 2021
作者: Duan, Pengqi Zheng, Yudong Lu, Jun College of Computer Science and Technology Heilongjiang University HLJU Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China
Even though pre-trained language models like BERT and XLNet have produced significant consequences on a variety of tasks of natural language processing, they are difficult to deploy in practical applications due to th... 详细信息
来源: 评论
A Weakly Supervised Semantic Segmentation Model with Enhanced CLIP Feature Extraction
A Weakly Supervised Semantic Segmentation Model with Enhance...
收藏 引用
International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Fanxuan Kong Jun Lu College of Computer Science and Technology Heilongjiang University Harbin China Jiaxiang Industrial Technology Research Institute of Heilongjiang University Jining China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China
This paper addresses the limitations of the Contrastive Language-Image Pre-training (CLIP) model’s image encoder and proposes a segmentation model WSSS-ECFE with enhanced CLIP feature extraction, aiming to improve th... 详细信息
来源: 评论
Top-k Graph Similarity Search Based on Hierarchical Inverted Index  11
Top-k Graph Similarity Search Based on Hierarchical Inverted...
收藏 引用
11th International Conference on Information Science and Technology, ICIST 2021
作者: Wang, Zhongqing Yang, Yan Zhong, Yingli Heilongjiang University School of Computer Science Technology Harbin China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China
Graph similarity search is an important research problem in many applications, such as finding result graphs that have a similar structure to a given entity in biochemistry, data mining, and pattern recognition. Top-k... 详细信息
来源: 评论
Visible-Infrared Image Fusion Based on Double- Density Wavelet and Thermal Exchange Optimization  5
Visible-Infrared Image Fusion Based on Double- Density Wavel...
收藏 引用
5th IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2021
作者: Guo, Hao Chen, Jingyu Yang, Xuan Jiao, Qingliang Liu, Ming Beijing Institute of Environmental Features Beijing China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China
Infrared and visible image fusion has been a hot issue in image fusion. However, the parameters and result image have many proposed. In this paper, a novel visible infrared image fusion algorithm based on double-densi... 详细信息
来源: 评论
Community Search in Spatial Uncertain Network
Community Search in Spatial Uncertain Network
收藏 引用
2021 Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2021
作者: Zhang, Wenqian Zhong, Yingli Yang, Yan School of Computer Science Technology Heilongjiang University Harbin150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin150080 China
Community search is to explore valuable target community structure from a large social network. In real community, every point has a geographic location information, and many edges are uncertain. Such a network is cal... 详细信息
来源: 评论
Cross-Modality Encoder Representations Based On External Attention Mechanism
Cross-Modality Encoder Representations Based On External Att...
收藏 引用
Neural Networks, Information and Communication Engineering (NNICE), International Conference on
作者: Yudong Zheng Jun Lu College of Computer Science and Technology Heilongjiang University Harbin China College of Computer Science and Technology Heilongjiang University Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China
With the prevalence of deep learning, people use multi-modality information for interpretation and reasoning. In this paper, a cross-modality encoder CMEEA (cross-modality encoder representation based on external atte... 详细信息
来源: 评论
A New Feature Fusion Method Based on Pre-Training Model for Sequence Labeling
A New Feature Fusion Method Based on Pre-Training Model for ...
收藏 引用
International Conference on Data Storage and Data Engineering (DSDE)
作者: Shichuan Yu Yan Yang School of computer science and technology Heilongjiang University Harbin China Heilongjiang Key Laboratory of Database and Parallel Computing Heilongjiang University Harbin China
To fuse vocabulary features into the pre-training model is the mainstream data feature processing method for sequence labelling tasks. In general, the feature fusion methods that have been proposed at present are dire...
来源: 评论
DMSA: DYNAMIC MULTI-SCALE UNSUPERVISED SEMANTIC SEGMENTATION BASED ON ADAPTIVE AFFINITY
arXiv
收藏 引用
arXiv 2023年
作者: Yang, Kun Lu, Jun College of Computer Science and Technology Heilongjiang University 150080 Harbin China Jiaxiang Industrial Technology Research Institute of HLJU Jining Shandong Province China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China
The proposed method in this paper proposes an end-to-end unsupervised semantic segmentation architecture DMSA based on four loss functions. The framework uses Atrous Spatial Pyramid Pooling (ASPP) module to enhance fe... 详细信息
来源: 评论
DMSA: Dynamic Multi-Scale Unsupervised Semantic Segmentation Based On Adaptive Affinity
DMSA: Dynamic Multi-Scale Unsupervised Semantic Segmentation...
收藏 引用
International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Kun Yang Jun Lu College of Computer Science and Technology Heilongjiang University Harbin China Jiaxiang Industrial Technology Research Institute of HLJU Jining China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China
The proposed method in this paper proposes an end-to-end unsupervised semantic segmentation architecture DMSA based on four loss functions. The framework uses Atrous Spatial Pyramid Pooling (ASPP) module to enhance fe... 详细信息
来源: 评论