MSK-UNET: A Modified U-Net Architecture Based on Selective Kernel with Multi-Scale Input for Pavement Crack Detection

计算机科学 核(代数) 卷积(计算机科学) 背景(考古学) 编码器 算法 棱锥(几何) 人工智能 数学 人工神经网络 古生物学 几何学 生物 操作系统 组合数学
作者
Xiaoliang Jiang,Jinyun Jiang,Jianping Yu,Jun Wang,Ban Wang
出处
期刊:Journal of Circuits, Systems, and Computers [World Scientific]
卷期号:32 (01) 被引量:13
标识
DOI:10.1142/s0218126623500068
摘要

Pavement crack condition is a vitally important indicator for road maintenance and driving safety. However, due to the interference of complex environment, such as illumination, shadow and noise, the automatic crack detection solution cannot meet the requirements of accuracy and efficiency. In this paper, we present an extended version of U-Net framework, named MSK-UNet, for pavement crack to solve these challenging problems. Specifically, first, the U-shaped network structure is chosen as the framework to extract more hierarchical representation. Second, we introduce selective kernel (SK) units to replace U-Net’s standard convolution blocks for obtaining the receptive fields with distinct scales. Third, multi-scale input layer establishes an image pyramid to retain more image context information at the encoder stage. Finally, a hybrid loss function including generalized Dice loss with Focal loss is employed. In addition, a regularization term is defined to reduce the impact of imbalance between positive and negative samples. To evaluate the performance of our algorithm, some tests were conducted on DeepCrack dataset, AsphaltCrack300 dataset and Crack500 dataset. Experimental results show that our approach can detect various crack types with diverse conditions, obtains a better performance in precision, recall and [Formula: see text]-score, with 97.43%, 96.95% and 97.01% precision values, 82.51%, 93.33% and 87.58% recall values and 95.33%, 99.24% and 98.55% [Formula: see text]-score values, respectively.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
xzy998发布了新的文献求助10
刚刚
1秒前
张元东发布了新的文献求助10
1秒前
1秒前
阁楼里猫发布了新的文献求助10
2秒前
烟花应助轻松不二采纳,获得10
2秒前
在水一方应助科研通管家采纳,获得10
2秒前
顾矜应助科研通管家采纳,获得10
3秒前
Camelia应助科研通管家采纳,获得10
3秒前
小二郎应助科研通管家采纳,获得10
3秒前
小蘑菇应助科研通管家采纳,获得10
3秒前
3秒前
wanci应助科研通管家采纳,获得30
3秒前
科研通AI2S应助科研通管家采纳,获得10
3秒前
SciGPT应助科研通管家采纳,获得10
3秒前
Jasper应助科研通管家采纳,获得10
3秒前
Xin发布了新的文献求助10
4秒前
wisper完成签到,获得积分20
5秒前
xs发布了新的文献求助10
7秒前
8秒前
天天发布了新的文献求助30
8秒前
思源应助Xuan_123456采纳,获得10
8秒前
彭于晏完成签到,获得积分0
8秒前
9秒前
9秒前
10秒前
生动谷蓝发布了新的文献求助10
10秒前
纯真黄蜂完成签到,获得积分10
11秒前
11秒前
Orange应助往返采纳,获得150
12秒前
12秒前
13秒前
轻松不二完成签到,获得积分10
13秒前
14秒前
elo发布了新的文献求助10
15秒前
小高发布了新的文献求助10
15秒前
16秒前
轻松不二发布了新的文献求助10
16秒前
ziwang发布了新的文献求助10
17秒前
高分求助中
【此为提示信息,请勿应助】请按要求发布求助,避免被关 20000
Production Logging: Theoretical and Interpretive Elements 3000
The Finite Element Method Its Basis and Fundamentals 2000
Am Rande der Geschichte : mein Leben in China / Ruth Weiss 1500
CENTRAL BOOKS: A BRIEF HISTORY 1939 TO 1999 by Dave Cope 1000
J'AI COMBATTU POUR MAO // ANNA WANG 660
Izeltabart tapatansine - AdisInsight 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3752718
求助须知:如何正确求助?哪些是违规求助? 3296271
关于积分的说明 10093218
捐赠科研通 3011165
什么是DOI,文献DOI怎么找? 1653623
邀请新用户注册赠送积分活动 788307
科研通“疑难数据库(出版商)”最低求助积分说明 752809