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The Power of Tiling for Small Object Detection
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019Deep neural network based techniques are state-of-the-art for object detection and classification with the help of the development in computational power and memory efficiency. Although these networks are adapted for mobile platforms with sacrifice in accuracy; the resolution increase in visual sources makes the problem even harder by raising the ...
F. Ozge Unel +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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Small Object Detection by Generative and Discriminative Learning
2020 25th International Conference on Pattern Recognition (ICPR), 2021With the development of deep convolutional neural networks (CNNs), the object detection accuracy has been greatly improved. But the performance of small object detection is still far from satisfactory, mainly because small objects are so tiny that the information contained in the feature map is limited.
Yi Gu +4 more
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The Detection of Orientation of Small Objects
Perception, 1997Visual information processing in primate cortex is based on a highly ordered representation of the surrounding world. In addition to the retinotopic mapping of the visual field, systematic variations of the orientation tuning of neurons are described electrophysiologically for the first stages of the visual stream.
J M Zanker, M P Davey
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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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Detection of small moving object by optical flow
Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol.II. Conference B: Pattern Recognition Methodology and Systems, 2003Deals with a method of detecting small moving objects in an image sequence. Although it is difficult to recognize small objects in a single image, if they are moving in an image sequence, it is easy to detect them, no matter how small they are. In order to detect small objects with robotic eyes, The authors propose a new interpretation of optical flow.
Takashi Hirai +3 more
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Mask-guided SSD for small-object detection
Applied Intelligence, 2020Detecting small objects is a challenging job for the single-shot multibox detector (SSD) model due to the limited information contained in features and complex background interference. Here, we increased the performance of the SSD for detecting target objects with small size by enhancing detection features with contextual information and introducing a ...
Chang Sun +3 more
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Ensemble Fusion for Small Object Detection
2023 18th International Conference on Machine Vision and Applications (MVA), 2023Hao-Yu Hou +7 more
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Small Object Detection in Highly Variable Backgrounds
2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA), 2019The analysis of imagery from outdoor remote sensing is a technique widely used for surveying and data gathering. This paper studies techniques to be deployed in small object localisation using Convolutional Neural Networks (CNN), with the aim to detect litter in outdoor non-urban imagery.
Michael Schembri, Dylan Seychell
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Small Object Detection in Aerial Images
2021 IEEE 14th International Conference on ASIC (ASICON), 2021Ruoyu Zhang +3 more
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