24 papers · ranked by Valyu relevance
Jing Yang, Shaobo Li, Zheng Wang, Hao Dong + 2 more
The detection of product defects is essential in quality control in manufacturing. This study surveys stateoftheart deep-learning methods in defect detection. First, we classify the defects of products, such as electronic components, pipes, welded parts, and textile materials, into categories. Second, recent mainstream…
Jaromír Klarák, Robert Andok, Peter Malík, Ivan Kuric + 4 more
'Mário Ritomský' 'Ivana Klačková' 'Hung-Yin Tsai' 'Sergio Toral Marín'] This paper proposes a new approach to defect detection system design focused on exact damaged areas demonstrated through visual data containing gear wheel images. The main advantage of the system is the capability to detect a wide range of patterns…
Jun Bai, Di Wu, Tristan Shelley, Peter Schubel + 4 more
Detection: Challenges, Solutions, and Future Prospects Authors: ['Jun Bai' 'Di Wu' 'Tristan Shelley' 'Peter Schubel' 'David Twine' 'John Russell' 'Xuesen Zeng' 'Zhang Ji'] JUN BAI, University of Southern Queensland, Toowoomba, Australia DI WU, University of Southern Queensland, Toowoomba, Australia TRISTAN SHELLEY…
Zelin Deng, Xiaolong Yan, Shengjun Zhang, Colleen P. Bailey
—A maximally stable extreme region (MSER) analysis based convolutional neural network (CNN) for unified defect detection framework is proposed in this paper. Our proposed framework utilizes the generality and stability of MSER to generate the desired defect candidates. Then a specific trained binary CNN classifier is…
Meishun Wu, Jinmin Peng, Xinyi Yu, Heng Xu + 2 more
Surface defects in industrial environments severely the impact product aesthetics, quality, and operational efficiency. Although deep learning approaches show promise, current architectures often demonstrate inadequate feature extraction in industrial settings. We introduce EFEN-YOLOv8, a novel defect detection…
Zijian Kuang, Xinran Tie, Lihang Ying, Shi Jin
—Visual defect detection is critical to ensure the quality of most products. However, the majority of small and medium-sized manufacturing enterprises still rely on tedious and error-prone human manual inspection. The main reasons include: 1) the existing automated visual defect detection systems require altering…
Qian Liu, Xiaohua Huang, Xiuyan Shao, Fei Hao
In the field of artificial intelligence, a large number of promising tools, such as condition-based maintenance, are available for large internal combustion engines. The cylinder liner, which is a key engine component, is subject to defects due to the manufacturing process. In addition, the cylinder liner…
Ming Chen, Yuqing Liu, Xing Wei, Zichen Zhang + 4 more
'Hengshou Sui' 'Bin Li' 'Sadiq H. Abdulhussain'] Solenoid connectors play important role in electronic stability system design, with the features of small size, low cost, fast response time and high reliability. The main production process challenge for solenoid connectors is the accurate detection of defects, which is…
V. Suma, Gopalakrishnan T.R. Nair
Software is a unique entity that has laid a strong impact on all other fields either related or not related to software. These include medical, scientific, business, educational, defence, transport, telecommunication to name a few. State-of-the-art professional domain activities demands the development of high quality…
Tianhe Xie, Rongyi Sun, Jiahao Zhang, Ruiqi Wang + 1 more
With development of economy, all industries have undergone earthshaking changes. Various new technologies are starting to be employed in all aspects of life, and graphic design is no exception. The use of computer graphics and image processing technologies in graphic design can substantially improve design efficiency…
Nadeem Nazer, Hongkuan Zhou, Lavdim Halilaj, Ylli Sadikaj + 1 more
Recent vision language models (VLMs) like CLIP have demonstrated impressive anomaly detection performance under significant distribution shift by utilizing high-level semantic information through text prompts. However, these models often neglect fine-grained details, such as which kind of anomalies, like "hole", "cut"…
Chou, Po-Heng, Wang, Chun-Chi + 1 more
—In this paper, we propose a YOLO-based deep learning (DL) model for automatic defect detection to solve the timeconsuming and labor-intensive tasks in industrial manufacturing. In our experiments, the images of metal sheets are used as the dataset for training the YOLO model to detect the defects on the surfaces and…
Desmond Kabus, Louise Arno, Lore Leenknegt, Alexander V. Panfilov + 1 more
Electrical waves that rotate in the heart organize dangerous cardiac arrhythmias. Finding the region around which such rotation occurs is one of the most important practical questions for arrhythmia management. For many years, the main method for finding such regions was so-called phase mapping, in which a continuous…
Arash Abbasi, Max J. Feldman, Jaebum Park, Katelyn Greene + 2 more
A novel deep learning algorithm is proposed for hollow heart detection which is an internal tuber defect. Hollow heart is one of many internal defects that decrease the market value of potatoes in the fresh market and food processing sectors. Susceptibility to internal defects like the hollow heart is influenced by…
Authors not listed
Assessing the susceptibility of stainless steel (SS) to pitting corrosion remains challenging due to the difficulty in identifying nanometre-scale imperfections in the passive surface films. Traditional analytical methods are costly, time-consuming, and limited to model systems with adequate signal-to-noise ratios. We…
Sumitabha Brahmachari, Andrew Dittmore, Yasuharu Takagi, Keir C. Neuman + 1 more
We present a statistical-mechanical model for stretched twisted double-helix DNA, where thermal fluctuations are treated explicitly from a Hamiltonian without using any scaling hypotheses. Our model applied to defect-free supercoiled DNA describes coexistence of multiple plectoneme domains in long DNA molecules at…
Nima Rafiee, Rahil Gholamipoor, Markus Kollmann
Recent progress in computer-aided technologies has had a considerable impact on helping experts with a reliable and fast diagnosis of abnormal samples. In particular, self-supervised and self-distillation techniques have advanced automated out-of-distribution (OOD) detection in the image domain. Further improvements in…
Paul Morris, Cory Simon
In many gas sensing tasks, we simply wish to become aware of gas compositions that deviate from normal, "business-as-usual" conditions. We provide a methodology, illustrated by example, to computationally predict the performance of a gas sensor array design for detecting anomalous gas compositions. Specifically, we…
Cong Ma, Carl Kingsford
Algorithms to infer isoform expression abundance from RNA-seq have been greatly improved in accuracy during the past ten years. However, due to incomplete reference transcriptomes, mapping errors, incomplete sequencing bias models, or mistakes made by the algorithm, the quantification model sometimes could not explain…
Authors not listed
Localized detection of hydrogen permeation in steel membranes is crucial for practical applications but remains challenging. We present a reflective microscopy (RM) approach combined with machine learning (ML)-driven image analysis to address this issue. Hydrogen permeation in press-hardened steel alters the…
Meng Jia, Troy Sorensen, Dorit Hammerling
We propose a generic, modular framework to optimize the placement of continuous monitoring sensors on oil and gas sites aiming to maximize the methane emissions detection efficiency. Our proposed framework substantially expands the problem scale compared to previous related studies and can be adapted for different…
Hongli Jiang, S. Hessam M. Mehr
The availability, portability, and low cost of electronic devices have made them a prime candidate for the rapid detection of chemical particles. Here we designed a chemical particle detection system based on a Raspberry Pi camera to detect micron droplets generated by ultrasonic atomizers. Through the analysis of…
William Daniels, Meng Jia, Dorit Hammerling
We propose a generic, modular framework for emission event detection, localization, and quantification on oil and gas production sites that uses concentration data collected by pointin-space continuous monitoring systems (CMS). The framework uses a gradient-based spike detection algorithm to estimate emission start and…
Carolina Cunha, Antónia Monteiro, Margarida Silveira
Butterflies are increasingly becoming model insects where basic questions surrounding the diversity of their color patterns are being investigated. Some of these color patterns consist of simple spots and eyespots. To accelerate the pace of research surrounding these discrete and circular pattern elements we developed…