Results 21 to 30 of about 11,183,951 (361)

Corner-Point and Foreground-Area IoU Loss: Better Localization of Small Objects in Bounding Box Regression

Sensors, 2023
Bounding box regression is a crucial step in object detection, directly affecting the localization performance of the detected objects. Especially in small object detection, an excellent bounding box regression loss can significantly alleviate the ...
Delong Cai, Zhaoyun Zhang, Zhi Zhang
doaj   +1 more source

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, Yang Liu, Yang Liu, Pengzhi Chu, Minglei Tong, Qingjie Kong   +5 more
doaj   +1 more source

UAV-YOLOv8: A Small-Object-Detection Model Based on Improved YOLOv8 for UAV Aerial Photography Scenarios

Italian National Conference on Sensors, 2023
Unmanned aerial vehicle (UAV) object detection plays a crucial role in civil, commercial, and military domains. However, the high proportion of small objects in UAV images and the limited platform resources lead to the low accuracy of most of the ...
G. Wang, Yanfei Chen, Pei An, Hanyu Hong, Jinghu Hu, Tiange Huang   +5 more
semanticscholar   +1 more source

E-YOLOv4-tiny: a traffic sign detection algorithm for urban road scenarios

Frontiers in Neurorobotics, 2023
IntroductionIn urban road scenes, due to the small size of traffic signs and the large amount of surrounding interference information, current methods are difficult to achieve good detection results in the field of unmanned driving.MethodsTo address the ...
Yanqiu Xiao, Yanqiu Xiao, Shiao Yin, Shiao Yin, Guangzhen Cui, Guangzhen Cui, Weili Zhang, Weili Zhang, Lei Yao, Lei Yao, Zhanpeng Fang, Zhanpeng Fang   +11 more
doaj   +1 more source

Let the loss impartial: a hierarchical unbiased loss for small object segmentation in high-resolution remote sensing images

European Journal of Remote Sensing, 2023
The progress in optical remote sensing technology presents both a possibility and challenge for small object segmentation task. However, the gap between human vision cognition and machine behavior still poses an inherent constrains to the interpretation ...
Qianpeng Chong, Mengying Ni, Jianjun Huang, Guangyi Wei, Ziyi Li, Jindong Xu   +5 more
doaj   +1 more source

Efficient Small Object Detection You Only Look Once: A Small Object Detection Algorithm for Aerial Images

Italian National Conference on Sensors
Aerial images have distinct characteristics, such as varying target scales, complex backgrounds, severe occlusion, small targets, and dense distribution.
Ao Tang, Jie Luo, Zhicheng Liu, Huahong Zuo, Yibo Wang, Ping Han   +5 more
core   +2 more sources

Pest Region Detection in Complex Backgrounds via Contextual Information and Multi-Scale Mixed Attention Mechanism

Agriculture, 2022
In precision agriculture, effective monitoring of corn pest regions is crucial to developing early scientific prevention strategies and reducing yield losses.
Wei Zhang, Youqiang Sun, He Huang, Haotian Pei, Jiajia Sheng, Po Yang   +5 more
doaj   +1 more source

An Anchor-Free Lightweight Object Detection Network

IEEE Access, 2023
Existing anchor-free object detection methods have achieved some amazing results, but these methods are relatively complex and the inference speed is also slow. In this paper, an anchor-free lightweight object detection network is proposed.
Weina Wang, Yunyan Gou
doaj   +1 more source

Small Object Recognition Algorithm of Grain Pests Based on SSD Feature Fusion

IEEE Access, 2021
The detection of grain pests is of great significance to grain storage. However, in practice, because the size of grain insects is too small to identify.
Zongwang Lyu, Huifang Jin, Tong Zhen, Fuyan Sun, Hui Xu   +4 more
doaj   +1 more source

Aggregation Signature for Small Object Tracking [PDF]

IEEE Transactions on Image Processing, 2020
Small object tracking becomes an increasingly important task, which however has been largely unexplored in computer vision. The great challenges stem from the facts that: 1) small objects show extreme vague and variable appearances, and 2) they tend to be lost easier as compared to normal-sized ones due to the shaking of lens. In this paper, we propose
Chunlei Liu 0001, Wenrui Ding, Jinyu Yang, Vittorio Murino, Baochang Zhang 0001, Jungong Han, Guodong Guo   +6 more
openaire   +4 more sources