Recognizing Hand-Woven Fabric Pattern Designs Based on Deep Learning

Puarungroj, Wichai; Boonsirisumpun, Narong

doi:10.1007/978-981-13-6861-5_28

Cited by 14 publications

(10 citation statements)

References 11 publications

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“…From a previous research study, Batik was established as a form of artistic expression with unique features that could become an identity or may become a cultural identity for either the region or the nation (Syakir et al, 2017). Accordingly, fabric pattern designs commonly represent the tradition and culture of local communities (Puarungroj & Boonsirisumpun, 2019). This proves the importance of understanding patterns used on fabric is important to preserve the cultural heritage and know better.…”

Section: Literature Reviewmentioning

confidence: 99%

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Stimulating Interactive Apps in Conserving Batik Block Pattern

Kamaruddin¹,

Satar²,

Rosli³

2021

IJARBSS

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Batik is a Malaysian culture where the motif and pattern represent our identity and cultural heritage. People prefer to dress elegantly and simply in contemporary society. Additionally, the current batik pattern lacks a robust Malaysian identity. The traditional element also struggles to develop a local identity due to the lack of a descriptive document describing the Malaysian design. This research aims to identify traditional Malaysian batik patterns and develop an interactive application that will aid in the preservation of Malaysian culture and heritage. This study collected data through a review of contextual documents, in-depth interviews, and online survey questionnaires by establishing that Malaysian batik contains numerous patterns that all Malaysians must preserve as part of the country's heritage. Our finding shows that the proposed batik apps have the potential to increase Malaysians' awareness of batik patterns while also contributing to the preservation of culture and heritage value. Individuals can use the app to search for information about batik easily. Furthermore, for the Jabatan Warisan Negara, which is part of the Ministry of Tourism Malaysia, the app will act as a medium for promoting one of Malaysia's cultural and heritage treasures, Batik design.

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Section: Literature Reviewmentioning

confidence: 99%

“…According to Puarungroj & Boonsirisumpun (2019), pattern design commonly represents local communities' traditions and culture. This is presented by example Indonesians place more importance on batik designs which reflect their identity.…”

Section: Literature Reviewmentioning

confidence: 99%

Stimulating Interactive Apps in Conserving Batik Block Pattern

Kamaruddin¹,

Satar²,

Rosli³

2021

IJARBSS

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“…[70] investigated the image-based recognition of eight different types of structure in knitted fabrics and achieved overall accuracies of up to 98.4% using a CNN. Other works focused on the recognition of patterns of woven fabrics, where a Residual Network architecture [71] achieved an up to 99.3% overall accuracy in distinguishing three different types of woven fabrics [72] and a 94.2% overall accuracy was achieved by a MobileNet architecture [73] in classifying 10 different patterns of silk fabrics [74]. Whereas all these works investigated the derivation of one single characteristic of images of fabrics, Meng and others [75] proposed a multi-task neural network to simultaneously locate individual yarns in a fabric and determine a float-point location map.…”

Section: Multi-task Learning With Training Samples For the Image-basementioning

confidence: 99%

From Silk to Digital Technologies: A Gateway to New Opportunities for Creative Industries, Traditional Crafts and Designers. The SILKNOW Case

et al. 2020

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Nowadays, cultural heritage is more than ever linked to the present. It links us to our cultural past through the conscious act of preserving and bequeathing to future generations, turning society into its custodian. The appreciation of cultural heritage happens not only because of its communicative power, but also because of its economic power, through sustainable development and the promotion of creative industries. This paper presents SILKNOW, an EU-H2002 funded project and its application to cultural heritage, as well as to creative industries and design innovation. To this end, it presents the use of image recognition tools applied to cultural heritage, through the interoperability of data in the open-access registers of silk museums and its presentation, analysis and creative process carried out by the design students of EASD Valencia as a case study, in the branches of jewellery and fashion project, inspired by the heritage of silk.

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“…As indicated in Fig. 4, MobileNets are based on an architecture that uses depth wise separable convolutions to build lightweight deep neural networks [17,[39][40][41]. In [17], the authors introduced two simple global hyper-parameters that effectively compensate for latency and accuracy.…”

Section: The Verification Step Based On Deep Learning Classifiersmentioning

confidence: 99%

Wind turbine tower detection using feature descriptors and deep learning

Abedini

Bahaghighat²,

Shoyan

2020

Facta Univ Electron Energ

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Wind Turbine Towers (WTTs) are the main structures of wind farms. They are costly devices that must be thoroughly inspected according to maintenance plans. Today, existence of machine vision techniques along with unmanned aerial vehicles (UAVs) enable fast, easy, and intelligent visual inspection of the structures. Our work is aimed towards developing a visionbased system to perform Nondestructive tests (NDTs) for wind turbines using UAVs. In order to navigate the flying machine toward the wind turbine tower and reliably land on it, the exact position of the wind turbine and its tower must be detected. We employ several strong computer vision approaches such as Scale-Invariant Feature Transform (SIFT), Speeded Up Robust Features (SURF), Features from Accelerated Segment Test (FAST), Brute-Force, Fast Library for Approximate Nearest Neighbors (FLANN) to detect the WTT. Then, in order to increase the reliability of the system, we apply the ResNet, MobileNet, ShuffleNet, EffNet, and SqueezeNet pre-trained classifiers in order to verify whether a detected object is indeed a turbine tower or not.

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Recognizing Hand-Woven Fabric Pattern Designs Based on Deep Learning

Cited by 14 publications

References 11 publications

Stimulating Interactive Apps in Conserving Batik Block Pattern

Stimulating Interactive Apps in Conserving Batik Block Pattern

From Silk to Digital Technologies: A Gateway to New Opportunities for Creative Industries, Traditional Crafts and Designers. The SILKNOW Case

Wind turbine tower detection using feature descriptors and deep learning

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