机构

• 自动化研究所 [27]
• 计算技术研究所 [12]
• 西安光学精密机械研究... [3]
• 地理科学与资源研究所 [2]
• 沈阳自动化研究所 [2]
• 力学研究所 [1]
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采集方式

• OAI收割 [52]

内容类型

• 期刊论文 [50]
• 会议论文 [2]

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• 2024 [10]
• 2023 [14]
• 2022 [14]
• 2021 [9]
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• Chemistry [1]
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筛选

浏览/检索结果: 共52条，第1-10条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 A Semantic-Consistent Few-Shot Modulation Recognition Framework for IoT Applications 期刊论文  OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2024, 页码: 12 作者:  Su, Jie;  Sun, Peng;  Jiang, Yuting;  Wen, Zhenyu;  Guo, Fangda   |  收藏  |  浏览/下载：3/0  |  提交时间：2024/12/06 Deep learning  few-shot learning (FSL)  Internet of Things (IoT)  signal processing   Which images to label for few-shot medical image analysis? 期刊论文  OAI收割 MEDICAL IMAGE ANALYSIS, 2024, 卷号: 96, 页码: 12 作者:  Quan, Quan;  Yao, Qingsong;  Zhu, Heqin;  Wang, Qiyuan;  Zhou, S. Kevin   |  收藏  |  浏览/下载：6/0  |  提交时间：2024/12/06 Few-shot  Contrastive learning  Augmentation   Emotion selectable end-to-end text-based speech editing 期刊论文  OAI收割 ARTIFICIAL INTELLIGENCE, 2024, 卷号: 329, 页码: 16 作者:  Wang, Tao;  Yi, Jiangyan;  Fu, Ruibo;  Tao, Jianhua;  Wen, Zhengqi   |  收藏  |  浏览/下载：34/0  |  提交时间：2024/07/03 Emotion selectable  Text-based speech editing  Emotion decoupling  Mask prediction  Few-shot learning  Text-to-speech   Hierarchical compositional representations for few-shot action recognition 期刊论文  OAI收割 COMPUTER VISION AND IMAGE UNDERSTANDING, 2024, 卷号: 240, 页码: 11 作者:  Li, Changzhen;  Zhang, Jie;  Wu, Shuzhe;  Jin, Xin;  Shan, Shiguang   |  收藏  |  浏览/下载：21/0  |  提交时间：2024/05/20 Action recognition  Few-shot learning  Hierarchical compositional representations  Body parts  EMD distance   Learning transferable cross-modality representations for few-shot hyperspectral and LiDAR collaborative classification 期刊论文  OAI收割 INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2024, 卷号: 126, 页码: 11 作者:  Dai, Mofan;  Xing, Shuai;  Xu, Qing;  Wang, Hanyun;  Li, Pengcheng   |  收藏  |  浏览/下载：25/0  |  提交时间：2024/02/26 Multimodal remote sensing data  Meta-learning  Few-shot learning  Cross-modality feature learning   Attentional Composition Networks for Long-Tailed Human Action Recognition 期刊论文  OAI收割 ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2024, 卷号: 20, 期号: 1, 页码: 18 作者:  Wang, Haoran;  Wang, Yajie;  Yu, Baosheng;  Zhan, Yibing;  Yuan, Chunfeng   |  收藏  |  浏览/下载：26/0  |  提交时间：2023/11/15 Compositional learning  long tail  few-shot  zero-shot  action recognition   Visual Semantic Segmentation Based on Few/Zero-Shot Learning: An Overview 期刊论文  OAI收割 IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 5, 页码: 1106-1126 作者:  Wenqi Ren;  Yang Tang;  Qiyu Sun;  Chaoqiang Zhao;  Qing-Long Han   |  收藏  |  浏览/下载：20/0  |  提交时间：2024/04/10 Computer vision  deep learning  few-shot learning  low-shot learning  semantic segmentation  zero-shot learning   A Real-Time Road Boundary Detection Approach in Surface Mine Based on Meta Random Forest 期刊论文  OAI收割 IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2024, 卷号: 9, 期号: 1, 页码: 1989-2001 作者:  Ai, Yunfeng;  Song, Ruiqi;  Huang, Chongqing;  Cui, Chenglin;  Tian, Bin   |  收藏  |  浏览/下载：12/0  |  提交时间：2024/07/22 Roads  Point cloud compression  Laser radar  Random forests  Metalearning  Surface treatment  Feature extraction  Road boundary detection  Point Cloud  meta learning  random forest  few shot classification  autonomous driving   Task-specific Part Discovery for Fine-grained Few-shot Classification 期刊论文  OAI收割 Machine Intelligence Research, 2024, 卷号: 21, 期号: 5, 页码: 954-965 作者:  Yongxian Wei;  Xiu-Shen Wei   |  收藏  |  浏览/下载：15/0  |  提交时间：2024/09/12 Fine-grained image recognition  few-shot learning  transductive learning  visual dictionary  part feature discovery   Binary Similarity Few-Shot Object Detection With Modeling of Hard Negative Samples 期刊论文  OAI收割 IEEE TRANSACTIONS ON MULTIMEDIA, 2024, 卷号: 26, 页码: 4805-4818 作者:  Lu, Yue;  Chen, Xingyu;  Wu, Zhengxing;  Tan, Min;  Yu, Junzhi   |  收藏  |  浏览/下载：20/0  |  提交时间：2024/05/30 Few-shot learning  object detection  computer vision  deep learning