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ADN for object detection [PDF]
IET Computer Vision, 2020 Owing to large‐scale diversity and location uncertainty in object detection, how to enrich semantic information has become an important issue that attracts a lot of concern.
Jinding Wang, Haifeng Hu, Xinlong Lu
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Detecting the unknown in Object Detection
CoRR, 2022 Object detection methods have witnessed impressive improvements in the last years thanks to the design of novel neural network architectures and the availability of large scale datasets. However, current methods have a significant limitation: they are able to detect only the classes observed during training time, that are only a subset of all the ...
Dario Fontanel +3 more
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Multiview-Learning-Based Generic Palmprint Recognition: A Literature Review
Mathematics, 2023 Palmprint recognition has been widely applied to security authentication due to its rich characteristics, i.e., local direction, wrinkle, and texture.
Shuping Zhao, Lunke Fei, Jie Wen
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IET Biometrics, 2022 Breast cancer accounts for the largest number of patients among all cancers in the world. Intervention treatment for early breast cancer can dramatically extend a woman's 5‐year survival rate.
Lilei Sun +6 more
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Two‐view attention‐guided convolutional neural network for mammographic image classification
CAAI Transactions on Intelligence Technology, 2023 Deep learning has been widely used in the field of mammographic image classification owing to its superiority in automatic feature extraction. However, general deep learning models cannot achieve very satisfactory classification results on mammographic ...
Lilei Sun +6 more
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CGENet: A Deep Graph Model for COVID-19 Detection Based on Chest CT
Biology, 2021 Accurate and timely diagnosis of COVID-19 is indispensable to control its spread. This study proposes a novel explainable COVID-19 diagnosis system called CGENet based on graph embedding and an extreme learning machine for chest CT images. We put forward
Si-Yuan Lu +3 more
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Survey of One-Stage Small Object Detection Methods in Deep Learning [PDF]
Jisuanji kexue yu tansuo, 2022 With the development of deep learning, object detection technology has gradually changed from traditional manual detection methods to deep neural network detection methods.
LI Kecen, WANG Xiaoqiang, LIN Hao, LI Leixiao, YANG Yanyan, MENG Chuang, GAO Jing
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Multi-Object Detection Using YOLOv7 Object Detection Algorithm on Mobile Device
Journal of Applied Engineering and Technological Science, 2023 This research discusses the importance of enhancing real-time object detection on mobile devices by introducing a new multi-object detection system that uses the quantified YOLOv7 model.
Patricia Citranegara Kusuma +1 more
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Review of Research on Imbalance Problem in Deep Learning Applied to Object Detection [PDF]
Jisuanji kexue yu tansuo, 2022 The current scheme of manually extracting features for object detection has been replaced by deep learning. Deep learning technology has greatly promoted the development of object detection technology.
REN Ning, FU Yan, WU Yanxia, LIANG Pengju, HAN Xi
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Spatiotemporal tubelet feature aggregation and object linking for small object detection in videos [PDF]
, 2022 This paper addresses the problem of exploiting spatiotemporal information to improve small object detection precision in video. We propose a two-stage object detector called FANet based on short-term spatiotemporal feature aggregation and long-term ...
Mucientes Molina, Manuel Felipe +2 more
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