Deep learning-based detection from the perspective of small or tiny objects: A survey

K Tong, Y Wu - Image and Vision Computing, 2022 - Elsevier
Detecting small or tiny objects is always a difficult and challenging issue in computer vision.
In this paper, we provide a latest and comprehensive survey of deep learning-based …

A survey of deep learning-based object detection methods in crop counting

Y Huang, Y Qian, H Wei, Y Lu, B Ling, Y Qin - Computers and Electronics in …, 2023 - Elsevier
Crop counting is a crucial step in crop yield estimation. By counting, crop growth status can
be accurately detected and adjusted, improving crop yield and quality. In recent years, with …

Towards large-scale small object detection: Survey and benchmarks

G Cheng, X Yuan, X Yao, K Yan, Q Zeng… - … on Pattern Analysis …, 2023 - ieeexplore.ieee.org
With the rise of deep convolutional neural networks, object detection has achieved
prominent advances in past years. However, such prosperity could not camouflage the …

YOLOv5-Tassel: Detecting tassels in RGB UAV imagery with improved YOLOv5 based on transfer learning

W Liu, K Quijano, MM Crawford - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) equipped with lightweight sensors, such as RGB cameras
and LiDAR, have significant potential in precision agriculture, including object detection …

An improved algorithm for small object detection based on YOLO v4 and multi-scale contextual information

SJ Ji, QH Ling, F Han - Computers and Electrical Engineering, 2023 - Elsevier
In real life, object detection is widely applied and plays a significant part in the field of
computer vision. However, when detecting small objects, the advanced You Only Look Once …

MSCAF-Net: A general framework for camouflaged object detection via learning multi-scale context-aware features

Y Liu, H Li, J Cheng, X Chen - IEEE Transactions on Circuits …, 2023 - ieeexplore.ieee.org
The aim of camouflaged object detection (COD) is to find objects that are hidden in their
surrounding environment. Due to the factors like low illumination, occlusion, small size and …

An efficient lightweight convolutional neural network for industrial surface defect detection

D Zhang, X Hao, D Wang, C Qin, B Zhao… - Artificial Intelligence …, 2023 - Springer
Since surface defect detection is significant to ensure the utility, integrality, and security of
productions, and it has become a key issue to control the quality of industrial products, which …

An ultrasmall bolt defect detection method for transmission line inspection

P Luo, B Wang, H Wang, F Ma, H Ma… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Bolt defect inspection is an important work in transmission line inspection. Due to the small
size of bolts in the transmission line inspection images, existing algorithms are difficult to …

A lightweight modified YOLOX network using coordinate attention mechanism for PCB surface defect detection

W Xuan, G Jian-She, H Bo-Jie… - IEEE sensors …, 2022 - ieeexplore.ieee.org
Surface defect detection for the printed circuit board (PCB) is essential in PCB
manufacturing. Existing defect detection networks have several problems: low detection …

[HTML][HTML] Cascade refinement extraction network with active boundary loss for segmentation of concrete cracks from high-resolution images

L Deng, H Yuan, L Long, P Chun, W Chen… - Automation in …, 2024 - Elsevier
Accurate extraction of cracks is important yet challenging in bridge inspection, particularly
that of tiny cracks captured from high-resolution (HR) images. This paper presents a crack …