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Attentional feature pyramid network for small object detection
Neural Networks, 2022Recent state-of-the-art detectors generally exploit the Feature Pyramid Networks (FPN) due to its advantage of detecting objects at different scales. Despite significant advances in object detection owing to the design of feature pyramids, it is still challenging to detect small objects with low resolution and dense distribution in complex scenes.
Kyungseo Min +2 more
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Small Object Detection Based on RVR
Proceedings of the 2017 International Conference on Robotics and Artificial Intelligence, 2017In the visual robotics area, we should dope out a solution to detect small objects. We need to explore much more precise detection methods to achieve better performance. In this paper, a small object detection method based on the Relevance Vector Regression (RVR) is proposed.
Ruiming Liu, Yong Liu, Jiawei Huang
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Context-Aware Block Net for Small Object Detection
IEEE Transactions on Cybernetics, 2022State-of-the-art object detectors usually progressively downsample the input image until it is represented by small feature maps, which loses the spatial information and compromises the representation of small objects. In this article, we propose a context-aware block net (CAB Net) to improve small object detection by building high-resolution and ...
Lisha Cui +7 more
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R-CNN for Small Object Detection
2017Existing object detection literature focuses on detecting a big object covering a large part of an image. The problem of detecting a small object covering a small part of an image is largely ignored. As a result, the state-of-the-art object detection algorithm renders unsatisfactory performance as applied to detect small objects in images.
Chenyi Chen +3 more
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Small Objects Detection Using Transformer-Cnn
SSRN Electronic Journal, 2022Chun-Liang Lin +2 more
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Image Factorization for Small Object Detection
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008Blind source separation techniques, specifically independent components analysis and Nonnegative Image Factorization have seen increasing use in the hyperspectral community for automated image exploitation. These techniques differ from more traditional image reduction methods such as principal components in that they make different statistical ...
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Survey of small object detection
Journal of Image and Graphics, 2023Xiaoying Pan +3 more
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Small object detection with random decision forests
2017 IEEE International Conference on Unmanned Systems (ICUS), 2017The random decision forests method is proposed to detect small object such as UAVs and aircrafts when they occupy a small portion of the field of view, with complex backgrounds, and are filmed by a camera that itself moves. The random decision forests is learned with discriminative decision trees, where every tree internal node is a discriminative ...
Juanjuan Ma +5 more
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GCPDFFNet: Small Object Detection for Rice Blast Recognition
Phytopathology®Early detection of rice blast disease is pivotal to ensure rice yield. We collected in situ images of rice blast and constructed a rice blast dataset based on variations in lesion shape, size, and color. Given that rice blast lesions are small and typically exhibit round, oval, and fusiform shapes, we proposed a small object detection model named ...
Dejin Xie +7 more
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Small object detection based on WavesNET
2022 10th International Conference on Information Systems and Computing Technology (ISCTech), 2022Zhengnan Li, Ji Zhao, Xiaowei Lu
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