Results 11 to 20 of about 159,708 (297)

Small Object Detection with Multiscale Features [PDF]

International Journal of Digital Multimedia Broadcasting, 2018
The existing object detection algorithm based on the deep convolution neural network needs to carry out multilevel convolution and pooling operations to the entire image in order to extract a deep semantic features of the image.
Guo X. Hu, Zhong Yang, Lei Hu, Li Huang, Jia M. Han   +4 more
doaj   +3 more sources

Efficient Small Object Detection You Only Look Once: A Small Object Detection Algorithm for Aerial Images. [PDF]

Sensors (Basel)
Aerial images have distinct characteristics, such as varying target scales, complex backgrounds, severe occlusion, small targets, and dense distribution.
Luo J, Liu Z, Wang Y, Tang A, Zuo H, Han P.   +5 more
europepmc   +3 more sources

Small Object Detection and Tracking: A Comprehensive Review [PDF]

Sensors, 2023
Object detection and tracking are vital in computer vision and visual surveillance, allowing for the detection, recognition, and subsequent tracking of objects within images or video sequences.
Behzad Mirzaei, Hossein Nezamabadi-pour, Amir Raoof, Reza Derakhshani   +3 more
doaj   +7 more sources

Small Object Detection in 3D Urban Scenes [PDF]

Jisuanji kexue, 2022
3D object detection is the core of semantic analysis in 3D urban scenes,but the existing object detection methods mainly focus on large objects such as buildings and roads,while the detection accuracy of these methods for small objects such as street ...
CHEN Jia-zhou, ZHAO Yi-bo, XU Yang-hui, MA Ji, JIN Ling-feng, QIN Xu-jia
doaj   +2 more sources

Dataset for small object detection with shadow (SODwS). [PDF]

Data Brief
Detecting small objects in aerial images poses several challenges, including issues with resolution limitations, scale variability, background clutter, and object occlusion.
Mat-Desa S, Mohd-Isa WN, Gomez-Krämer P, Roslee M, Hashim N, Abdullah J, Ali A, Che-Embi Z, Ibrahim A.   +8 more
europepmc   +4 more sources

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, Jianzhong Wang, Kemeng Bai, Yong Sun   +3 more
doaj   +2 more sources

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
doaj   +2 more sources

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
doaj   +2 more sources

Improved Small Object Detection Algorithm CRL-YOLOv5

Sensors
Detecting small objects in images poses significant challenges due to their limited pixel representation and the difficulty in extracting sufficient features, often leading to missed or false detections.
Zhiyuan Wang, Shujun Men, Yuntian Bai, Yutong Yuan, Jiamin Wang, Kanglei Wang, Lei Zhang   +6 more
doaj   +2 more sources

R-CNN for Small Object Detection

, 2016
Existing 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.
Chen, Chenyi, Chenyi Chen, Liu, Ming-Yu, Xiao, Jianxiong, Jianxiong Xiao, Oncel Tuzel, Ming-Yu Liu, Tuzel, Oncel   +7 more
core   +2 more sources