2023
DOI: 10.1016/j.infrared.2023.104852
|View full text |Cite
|
Sign up to set email alerts
|

Infrared maritime target detection based on edge dilation segmentation and multiscale local saliency of image details

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 47 publications
0
2
0
Order By: Relevance
“…The performance evaluation metrics of the model in this paper mainly use the mean pixel accuracy (mPA), mean intersection, and merger ratio (mIOU) to assess image segmentation model performance. Among them, mPA measures the average accuracy of the model in correctly predicting the pixels of each category-the higher the mPA value indicates, the better the pixel prediction accuracy of the model-which is calculated as shown in Equation (2). mIOU measures the segmentation accuracy of the model by calculating the ratio of the intersection and concatenation of the predicted segmentation results to the real segmentation results, with higher metrics indicating that the predicted results overlap with the real results and the model's segmentation effect is better.…”
Section: Indicators For Model Evaluationmentioning
confidence: 99%
See 1 more Smart Citation
“…The performance evaluation metrics of the model in this paper mainly use the mean pixel accuracy (mPA), mean intersection, and merger ratio (mIOU) to assess image segmentation model performance. Among them, mPA measures the average accuracy of the model in correctly predicting the pixels of each category-the higher the mPA value indicates, the better the pixel prediction accuracy of the model-which is calculated as shown in Equation (2). mIOU measures the segmentation accuracy of the model by calculating the ratio of the intersection and concatenation of the predicted segmentation results to the real segmentation results, with higher metrics indicating that the predicted results overlap with the real results and the model's segmentation effect is better.…”
Section: Indicators For Model Evaluationmentioning
confidence: 99%
“…In recent years, with the rapid development of deep learning, semantic segmentation [1], target detection [2], and image classification [3] have also made significant progress. Among them, in computer vision, semantic segmentation is a very important direction, and the main method used is to judge the category that this image belongs to by the pixels that have been labelled in the image.…”
Section: Introductionmentioning
confidence: 99%