中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
自动化研究所 [3]
地理科学与资源研究所 [1]
合肥物质科学研究院 [1]
采集方式
OAI收割 [5]
内容类型
期刊论文 [5]
发表日期
2024 [2]
2023 [1]
2022 [1]
2020 [1]
学科主题
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Towards interpreting machine learning models for understanding the relationship between vegetation growth and climate factors: A case study of the Anhui Province, China
期刊论文
OAI收割
ECOLOGICAL INDICATORS, 2024, 卷号: 167
作者:
Bao, Nana
;
Peng, Kai
;
Yan, Xingting
;
Lu, Yanxi
;
Liu, Mingyu
  |  
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2024/11/20
Vegetation index
Climate
Machine learning
Interpretable methods
Anhui Province
Interpretability in Sentiment Analysis: A Self-Supervised Approach to Sentiment Cue Extraction
期刊论文
OAI收割
APPLIED SCIENCES-BASEL, 2024, 卷号: 14, 期号: 7, 页码: 23
作者:
Sun, Yawei
;
He, Saike
;
Han, Xu
;
Luo, Yan
  |  
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2024/07/03
sentiment cue extraction
self-supervised learning
interpretable machine learning
Unraveling the mode substitution of dockless bike-sharing systems and its determinants: A trip level data-driven interpretation
期刊论文
OAI收割
SUSTAINABLE CITIES AND SOCIETY, 2023, 卷号: 98, 页码: 104820
作者:
Gao, Kun
;
Li, Aoyong
;
Liu, Yang
;
Gil, Jorge
;
Bie, Yiming
  |  
收藏
  |  
浏览/下载:23/0
  |  
提交时间:2024/01/04
Micromobility
Mode substitution
Big data analysis
Built environment
Interpretable machine learning
Towards Interpretable Defense Against Adversarial Attacks via Causal Inference
期刊论文
OAI收割
Machine Intelligence Research, 2022, 卷号: 19, 期号: 3, 页码: 209-226
作者:
Min Ren
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2024/04/23
Adversarial sample
adversarial defense
causal inference
interpretable machine learning
transformers
Bidirectional Attention-Recognition Model for Fine-Grained Object Classification
期刊论文
OAI收割
IEEE TRANSACTIONS ON MULTIMEDIA, 2020, 卷号: 22, 期号: 7, 页码: 1785-1795
作者:
Liu, Chuanbin
;
Xie, Hongtao
;
Zha, Zhengjun
;
Yu, Lingyun
;
Chen, Zhineng
  |  
收藏
  |  
浏览/下载:46/0
  |  
提交时间:2020/08/03
Fine-grained object classification
interpretable machine learning
visual attention
pattern recognition
data augmentation