P-value analysis of YOLOV8-DGS compared with YOLOv8.

Figshare2025-05-22 更新2026-04-28 收录

目标检测模型评估

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数据链接：

https://figshare.com/articles/dataset/P-value_analysis_of_YOLOV8-DGS_compared_with_YOLOv8_/29131842 数据链接链接失效反馈

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资源简介：

P-value analysis of YOLOV8-DGS compared with YOLOv8.

创建时间：

2025-05-22

DUT-OMRON

计算机视觉

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我们引入了一个带有自然图像的新数据库DUT-OMRON，用于研究在显着目标检测和眼睛注视预测中更适用且更可靠的方法。建议的数据库由从140,000多个图像中手动选择的5,168高质量图像组成。我们将图像的大小调整为400 × x或x × 400像素，其中x小于400。我们数据库的图像具有一个或多个显着对象和相对复杂的背景。我们总共有25名参与者来收集地面真相，每张图片有5名参与者的标签。他们都有

OpenDataLab2026-07-12 更新3530

Quantitative comparison of our proposed modified residual architecture with 9 traditional bottom-up saliency methods.

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模型性能比较

Text in bold denotes the best results.

NIAID Data Ecosystem20

Accuracy, standard deviation and p-values.

性能评估

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The accuracy is the average across the 20 runs with different random data partitions. P-values are calculated using the optimized custom CNN as pivot.

NIAID Data Ecosystem10

p-values obtained after performing t-test using the baseline models for the 4-class classification protocol.

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分类评估

p-values obtained after performing t-test using the baseline models for the 4-class classification protocol.

Figshare2022-10-14 更新20

Numbers of significant pairs among 48 risk factor-disease pairs at the significance cutoff of p-value < 0.001.

流行病学关联分析

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Numbers of significant pairs among 48 risk factor-disease pairs at the significance cutoff of p-value

Figshare2021-11-18 更新10