Deep Learning-Based Crack Detection: A Survey

Nguyen, Son Dong; Tran, Thai Son; Tran, Van Phuc; Lee, Hyun Jong; Piran, Md. Jalil; Le, Van Phuc

doi:10.1007/s42947-022-00172-z

Cited by 23 publications

(13 citation statements)

References 60 publications

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“…Zhu et al [60] and Nguyen and Tran [61] provided an advancement and challenge in the making of high-quality bitumen. Based on this information, bitumen modifications with various polymers were incorporated through one of two methods (dry and wet) to improve the constitutive properties of bituminous binders [62].…”

Section: Methods For Incorporation Of Polymer In Bitumenmentioning

confidence: 99%

“…Nguyen and Tran [61] and Cao [63] used this method of direct incorporation of the polymer as a modifier, partly substituting the proportion of fine aggregate. According to the rutting test and the indirect tensile test, adding waste polymers to dry-process asphalt mixes might increase their resistance to permanent deformation at high temperatures and cracking at low temperatures.…”

Section: The Dry Processmentioning

confidence: 99%

“…According to the rutting test and the indirect tensile test, adding waste polymers to dry-process asphalt mixes might increase their resistance to permanent deformation at high temperatures and cracking at low temperatures. This process is useful for enhancing the paving nature of the PMB [61,63].…”

Section: The Dry Processmentioning

confidence: 99%

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A Review on Virgin or Waste Polymers in Bitumen Modification for Ageing and Rejuvenation

Rashid,

Mudavath,

Chandra

et al. 2024

Chem Eng & Technol

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The physicochemical behavior of polymer‐modified binders suggests suitability for rejuvenating aged pavements and meets base bitumen parameters. The strengthening effect is mainly due to their electronic structures, which interact with asphaltene via CH‐π interactions and crosslinkage reaction with S–H and O–H bonds of base bitumen, along with the virgin and waste polymers used. The functional groups in bitumen play a vital role in enhanced paving resistance after modification. This review aims to provide an overview of the current knowledge on the role of polymers in bitumen modification and to identify research gaps. It also discusses underutilized technologies, methods, and future research perspectives to implement more effective road networks for an environmentally sustainable development.

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Section: Methods For Incorporation Of Polymer In Bitumenmentioning

confidence: 99%

Section: The Dry Processmentioning

confidence: 99%

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A Review on Virgin or Waste Polymers in Bitumen Modification for Ageing and Rejuvenation

Rashid,

Mudavath,

Chandra

et al. 2024

Chem Eng & Technol

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“…Passive video forensic techniques are used here to assess the validity of a video by obtaining features from it. As a result, the scientific community has been paying close attention to passive video forgery detection systems in recent years [ 133 , 168 ].…”

Section: Introductionmentioning

confidence: 99%

A comprehensive taxonomy on multimedia video forgery detection techniques: challenges and novel trends

El-Shafai,

Fouda,

El-Rabaie

et al. 2023

Multimed Tools Appl

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Thousands of videos are posted on websites and social media every day, including Twitter, Facebook, WhatsApp, Instagram, and YouTube. Newspapers, law enforcement publications, criminal investigations, surveillance systems, Banking, the museum, the military, imaging in medicine, insurance claims, and consumer photography are just a few examples of places where important visual data may be obtained. Thus, the emergence of powerful processing tools that can be easily made available online poses a huge threat to the authenticity of videos. Therefore, it’s vital to distinguish between true and fake data. Digital video forgery detection techniques are used to validate and check the realness of digital video content. Deep learning algorithms lately sparked a lot of interest in the field of digital forensics, such as Recurrent Neural Networks (RNN), Deep Convolutional Neural Networks (DCNN), and Adaptive Neural Networks (ANN). In this paper, we give a soft taxonomy as well as a thorough overview of recent research on multimedia falsification detection systems. First, the basic knowledge needed to comprehend video forgery is provided. Then, a summary of active and passive video manipulation detection approaches is provided. Anti-forensics, compression video methods, datasets required for video forensics, and challenges of video detection approaches are also addressed. Following that, we presented an overview of deepfake, and the datasets required for detection were also provided. Also, helpful software packages and forensics tools for video detection are covered. In addition, this paper provides an overview of video analysis tools that are used in video forensic applications. Finally, we highlight research difficulties as well as interesting research avenues. In short, this survey provides detailed information and a broader investigation to extract data and detect fraud video contents under one umbrella.

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“…The deep learning method for asphalt pavement crack identification is summarized by Nguyen et al. (2022), and the data volume and quality are the key factors for model improvement, mainly supervised learning, which takes a lot of time. It is believed that the model based on deep learning is very suitable for detecting cracks on the pavement (Balaji et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

Cross‐entropy‐based adaptive fuzzy control for visual tracking of road cracks with unmanned mobile robot

Zhang,

Yang,

Wang

et al. 2023

Computer aided Civil Eng

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Visual tracking of road cracks in unstructured road environment was, is, and remains a crucial and challenging task, which plays a vital role in accurate crack sealing for automated road cracks repair. However, many problems have not been well solved in existing automated road cracks repair, such as the low automation due to partial dependence on manual and the interrupted traffic flow caused by the heavy equipment used. In this article, a cross‐entropy‐based adaptive fuzzy control (CEAFC) method is proposed, which reaches visual tracking with unmanned mobile robot (VT‐UMbot) for road cracks. Specifically, the CEAFC method uses cross‐entropy optimization iteration to tune parameters for the tracking controller, and fuzzy logic is constructed to explore robustness improvement. Moreover, a framework of VT‐UMbot based on a four‐wheel independent differential drive is established, and visual servo and tracking control are integrated into the system. Our experiment shows that the proposed method is extensively evaluated on three road cracks scenarios and achieves state‐of‐the‐art performance with high efficiency.

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Deep Learning-Based Crack Detection: A Survey

Cited by 23 publications

References 60 publications

A Review on Virgin or Waste Polymers in Bitumen Modification for Ageing and Rejuvenation

A Review on Virgin or Waste Polymers in Bitumen Modification for Ageing and Rejuvenation

A comprehensive taxonomy on multimedia video forgery detection techniques: challenges and novel trends

Cross‐entropy‐based adaptive fuzzy control for visual tracking of road cracks with unmanned mobile robot

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