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检索条件"主题词=Few-Shot Object Detection"
128 条 记 录,以下是111-120 订阅
排序:
A Survey of Deep Learning for Low-shot object detection
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ACM COMPUTING SURVEYS 2024年 第5期56卷 1-37页
作者: Huang, Qihan Zhang, Haofei Xue, Mengqi Song, Jie Song, Mingli Zhejiang Univ 38 Zheda Rd Hangzhou Zhejiang Peoples R China
object detection has achieved a huge breakthrough with deep neural networks and massive annotated data. However, current detection methods cannot be directly transferred to the scenario where the annotated data is sca... 详细信息
来源: 评论
Contrastive JS: A Novel Scheme for Enhancing the Accuracy and Robustness of Deep Models
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IEEE TRANSACTIONS ON MULTIMEDIA 2023年 25卷 7881-7893页
作者: Xing, Weiwei Yao, Jie Liu, Zixia Liu, Weibin Zhang, Shunli Wang, Liqiang Beijing Jiaotong Univ Sch Software Engn Beijing 100044 Peoples R China Beijing Informat Sci & Technol Univ Sch Informat Management Beijing 100192 Peoples R China Beijing Jiaotong Univ Sch Comp & Informat Technol Beijing 100044 Peoples R China Univ Cent Florida Dept Comp Sci Orlando FL 32816 USA
Deep learning technologies have been applied in various computer vision tasks in recent years. However, deep models suffer performance decay when some unforeseen data are contained in the testing dataset. Although dat... 详细信息
来源: 评论
FS-OreDet: Feature enhancement and relationship exploration for boosting few-shot object detector of ore images
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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年 第PartE期133卷
作者: Sun, Guodong Cheng, Le Liu, Jinyu Peng, Yuting Xu, Chengming Fu, Yanwei Wu, Bo Zhang, Yang Hubei Univ Technol Sch Mech Engn Wuhan 430068 Peoples R China Beijing Key Lab Proc Automat Min & Met State Key Lab Intelligent Optimized Mfg Mining & M Beijing 102628 Peoples R China Nanjing Univ Natl Key Lab Novel Software Technol Nanjing 210023 Peoples R China Fudan Univ Sch Data Sci Shanghai 200433 Peoples R China Chinese Acad Sci Shanghai Adv Res Inst Shanghai 201210 Peoples R China Hubei Univ Technol Hubei Key Lab Modern Mfg Qual Engn Wuhan 430068 Peoples R China
In the ore beneficiation process, large block detection is necessary to ensure production safety. This typically involves identifying oversized ore on the conveyor belt and preventing material blockage accidents in th... 详细信息
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Meta-DETR: Image-Level few-shot detection With Inter-Class Correlation Exploitation
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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2023年 第11期45卷 12832-12843页
作者: Zhang, Gongjie Luo, Zhipeng Cui, Kaiwen Lu, Shijian Xing, Eric P. Nanyang Technol Univ Sch Comp Sci & Engn Singapore 639798 Singapore Carnegie Mellon Univ Sch Comp Sci Pittsburgh PA 15213 USA Mohamed bin Zayed Univ Artificial Intelligence Abu Dhabi U Arab Emirates
few-shot object detection has been extensively investigated by incorporating meta-learning into region-based detection frameworks. Despite its success, the said paradigm is still constrained by several factors, such a... 详细信息
来源: 评论
Yolo-sd: simulated feature fusion for few-shot industrial defect detection based on YOLOv8 and stable diffusion
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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2024年 第10期15卷 4589-4601页
作者: Wen, Yihao Wang, Li Taiyuan Univ Technol Coll Comp Sci & Technol Coll Data Sci 79 Yingze West St Taiyuan 030024 Shanxi Province Peoples R China
Defect detection from images, an important application in the development of the industrial internet, has been gaining increasing attention due to its close relationship with product quality in industrial production. ... 详细信息
来源: 评论
Online visual end-to-end detection monitoring on surface defect of aluminum strip under the industrial few-shot condition
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JOURNAL OF MANUFACTURING SYSTEMS 2023年 70卷 31-47页
作者: Ma, Zhuxi Li, Yibo Huang, Minghui Deng, Nanzhou Cent South Univ Sch Mech & Elect Engn Changsha 410083 Hunan Peoples R China Cent South Univ Light Alloy Res Inst Changsha 410083 Hunan Peoples R China
Surface defect detection systems based on deep learning are employed in the manufacturing system, and their good detection performance largely relies on abundant annotated data. Nevertheless, industrial datasets are o... 详细信息
来源: 评论
ITFD: an instance-level triplet few-shot detection network under weighted pair-resampling
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APPLIED INTELLIGENCE 2023年 第19期53卷 22728-22742页
作者: Chen, Xin Peng, Chaoyong Qiu, Chunrong Luo, Lin Huang, Deqing Liu, Ziyi Southwest Jiaotong Univ Sch Phys Sci & Technol 111Sect 1North Erhuan Rd Chengdu 610036 Sichuan Peoples R China Southwest Jiaotong Univ Inst Syst Sci & Technol Sch Elect Engn 999 Xian Rd Chengdu 611756 Sichuan Peoples R China
few-shot object detection has been widely applied in industrial applications, endangered detection, tumor lesion detection, etc. Although many excellent few-shot detection models have been proposed recently, intra-cla... 详细信息
来源: 评论
IRA-FSOD: Instant-Response and Accurate few-shot object Detector
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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2023年 第11期33卷 6912-6923页
作者: Huang, Junying Cao, Junhao Lin, Liang Zhang, Dongyu Sun Yat Sen Univ Dept Comp Sci & Engn Guangzhou 510275 Peoples R China
Aiming at recognizing and localizing objects of novel categories with just a few reference samples, few-shot object detection (FSOD) is quite a challenging task. Previous works rely heavily on the fine-tuning process ... 详细信息
来源: 评论
Multi-task Self-supervised few-shot detection  6th
Multi-task Self-supervised Few-Shot Detection
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6th Chinese Conference on Pattern Recognition and Computer Vision (PRCV)
作者: Zhang, Guangyong Duan, Lijuan Wang, Wenjian Gong, Zhi Ma, Bian Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Beijing Key Lab Trusted Comp Beijing 100124 Peoples R China Natl Engn Lab Crit Technol Informat Secur Classif Beijing 100124 Peoples R China
few-shot object detection involves detecting novel objects with only a few training samples. But very few samples are difficult to cover the bias of the new class in the deep model. To address the issue, we use self-s... 详细信息
来源: 评论
Robust Temporally-Coherent Strategy for few-shot Video Instance Segmentation  29
Robust Temporally-Coherent Strategy for Few-shot Video Insta...
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IEEE International Conference on Image Processing (ICIP)
作者: Wang, Qiuyue Zhang, Songyang He, Xuming ShanghaiTech Univ Shanghai Peoples R China
Traditional video instance segmentation (VIS) aims to detect, segment, and track object instances from a known class set in videos. In real-world applications, however, video instance segmentation typically need to co... 详细信息
来源: 评论