Results 21 to 30 of about 151,483 (263)
Lightweight multi-scale network for small object detection [PDF]
PeerJ Computer Science, 2022 Small object detection is widely used in the real world. Detecting small objects in complex scenes is extremely difficult as they appear with low resolution.
Li Li, Bingxue Li, Hongjuan Zhou
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Small Object Detection Based on Improved YOLOv7 [PDF]
Jisuanji gongcheng, 2023 Despite advancements in object detection technology, Small Object Detection(SOD) is still difficult to research.To address the challenge of easily missing detection in the process of object detection, this study proposes an improved YOLOv7 object ...
QI Linglong, GAO Jianling
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Small Object Detection Based on Deep Learning for Remote Sensing: A Comprehensive Review
Remote Sensing, 2023 With the accelerated development of artificial intelligence, remote-sensing image technologies have gained widespread attention in smart cities. In recent years, remote sensing object detection research has focused on detecting and counting small dense ...
Xuan Wang +4 more
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Centered Multi-Task Generative Adversarial Network for Small Object Detection
Sensors, 2021 Despite the breakthroughs in accuracy and efficiency of object detection using deep neural networks, the performance of small object detection is far from satisfactory. Gaze estimation has developed significantly due to the development of visual sensors.
Hongfeng Wang +3 more
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Focus-and-Detect: A small object detection framework for aerial images
Signal Processing: Image Communication, 2022 Despite recent advances, object detection in aerial images is still a challenging task. Specific problems in aerial images makes the detection problem harder, such as small objects, densely packed objects, objects in different sizes and with different orientations.
Onur Can Koyun +3 more
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MC-YOLOv5: A Multi-Class Small Object Detection Algorithm
Biomimetics, 2023 The detection of multi-class small objects poses a significant challenge in the field of computer vision. While the original YOLOv5 algorithm is more suited for detecting full-scale objects, it may not perform optimally for this specific task. To address
Haonan Chen +6 more
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SSDLiteX: Enhancing SSDLite for Small Object Detection
Applied Sciences, 2023 Object detection in many real applications requires the capability of detecting small objects in a system with limited resources. Convolutional neural networks (CNNs) show high performance in object detection, but they are not adequate to resource ...
Hyeong-Ju Kang
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Augmentation for small object detection
9th International Conference on Advances in Computing and Information Technology (ACITY 2019), 2019 In recent years, object detection has experienced impressive progress. Despite these improvements, there is still a significant gap in the performance between the detection of small and large objects. We analyze the current state-of-the-art model, Mask-RCNN, on a challenging dataset, MS COCO.
Mate Kisantal +4 more
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Adaptive Feature Fusion for Small Object Detection
Applied Sciences, 2022 In order to alleviate the situation that small objects are prone to missed detection and false detection in natural scenes, this paper proposed a small object detection algorithm for adaptive feature fusion, referred to as MMF-YOLO.
Qi Zhang, Hongying Zhang, Xiuwen Lu
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Small Object Detection via Pixel Level Balancing With Applications to Blood Cell Detection
Frontiers in Physiology, 2022 Object detection technology has been widely used in medical field, such as detecting the images of blood cell to count the changes and distribution for assisting the diagnosis of diseases.
Bin Hu +5 more
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