A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Filters
A Case Study on Attribute Recognition of Heated Metal Mark Image Using Deep Convolutional Neural Networks
2018
Sensors
Preserved Fulltext
This paper presents a case study on attribute recognition of the heated metal mark image using computer vision and machine learning technologies. The proposed work is composed of three parts. ...
Feature representation and classifier construction methods are introduced based on deep convolutional neural networks. Finally, the experimental evaluation is carried out. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s18061871
pmid:29880774
pmcid:PMC6022075
fatcat:dt2xii23mjddzayrmccaegg5n4
Heated Metal Mark Attribute Recognition Based on Compressed CNNs Model
2019
Applied Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
This study considered heated metal mark attribute recognition based on compressed convolutional neural networks (CNNs) models. ...
Based on our previous works, the heated metal mark image benchmark dataset was further expanded. State-of-the-art lightweight CNNs models were selected. ...
Our previous work performs a case study on heated metal attribute recognition based on CNNs [25] . We analyzed and selected seven heated metal attributes. ...
doi:10.3390/app9091955
fatcat:vi5srtm7grfkde4xtrfzv2ikne
2019 Index IEEE Transactions on Semiconductor Manufacturing Vol. 32
2019
IEEE transactions on semiconductor manufacturing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
., +, TSM May
2019 190-198
Image retrieval
Wafer Defect Pattern Recognition and Analysis Based on Convolutional
Neural Network. ...
., +, TSM Aug. 2019 302-309
Wafer Defect Pattern Recognition and Analysis Based on Convolutional
Neural Network. ...
Profitability A Productivity-Oriented Wafer Map Optimization Using Yield Model Based on Machine Learning. ...
doi:10.1109/tsm.2019.2958442
fatcat:e276xgw6gbbdlc4fy2ldbrd4py
Using Deep Learning to Detect Defects in Manufacturing: A Comprehensive Survey and Current Challenges
2020
Materials
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Third, we summarize and analyze the application of ultrasonic testing, filtering, deep learning, machine vision, and other technologies used for defect detection, by focusing on three aspects, namely method ...
The detection of product defects is essential in quality control in manufacturing. This study surveys stateoftheart deep-learning methods in defect detection. ...
The deep residual network adds a residual module on the basis of the convolutional neural network. ...
doi:10.3390/ma13245755
pmid:33339413
pmcid:PMC7766692
fatcat:egyrdqjmqvebvoeaqf5yyi3cxm
Short Circuit Recognition for Metal Electrorefining Using an Improved Faster R-CNN With Synthetic Infrared Images
2021
Frontiers in Neurorobotics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is text/html.
This paper is concerned with the problem of short circuit detection in infrared image for metal electrorefining with an improved Faster Region-based Convolutional Neural Network (Faster R-CNN). ...
Raw infrared images without fault are used as backgrounds. By simulating the other two key variables on the background, different classes of objects are synthesized. ...
Robust license plate recognition using neural networks trained on synthetic images. ...
doi:10.3389/fnbot.2021.751037
pmid:34899228
pmcid:PMC8662818
fatcat:fqzpi7rmwzgyjbg5uxbdjqboxi
Intelligent Localization of Transformer Internal Degradations Combining Deep Convolutional Neural Networks and Image Segmentation
2019
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
In this study, an efficient fault localization method for transformer internal thermal faults was proposed by introducing different deep convolutional neural networks (CNNs) and image segmentation. ...
The transformer is one of the critical power devices, its intelligent monitoring and fault positioning require indepth studies. ...
Fault diagnosis accuracies are limited by the lack of fault samples, which is obvious when using deep Convolutional Neural Networks (CNNs). ...
doi:10.1109/access.2019.2916461
fatcat:6blrerabjfguji5g3s6lcajjue
Strip Steel Surface Defects Classification Based on Generative Adversarial Network and Attention Mechanism
2022
Metals
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
In response to this, this paper implements accurate classification of strip steel surface defects based on generative adversarial network and attention mechanism. ...
By expanding the number of samples from 1360 to 3773, the generated images can be further used for training classification algorithm. ...
[12] proposed an end-toend recognition system based on symmetric surround saliency map and deep convolutional neural network (CNN). ...
doi:10.3390/met12020311
doaj:971767c44879452fa5323200426e74d3
fatcat:ejom3typgngntlgtwxavptcmau
Deep Learning-Guided Surface Characterization for Autonomous Hydrogen Lithography
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
We trained a convolutional neural network to locate and differentiate between surface features of the technologically relevant hydrogen-terminated silicon surface imaged using a scanning tunneling microscope ...
Here we present an automation method for the identification of defects prior to atomic fabrication via hydrogen lithography using deep learning. ...
Subsequent model retraining was done using a learning rate of 0.001 which very slightly improved network performance in this case. ...
arXiv:1902.08818v2
fatcat:4emwlxafz5gntfhvtpundqcjya
2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57
2019
IEEE Transactions on Geoscience and Remote Sensing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
., Incorporating Temporary Coherent Li, X., Yeo, T.S., Yang, Y., Chi, C., Zuo, F., Hu, X., and Pi, Y., Refo-cusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight SAR Imaging on Arbitrary ...
., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674 Hu, C., Zhang, ...
Radar-Based Human Gait Recognition Using Dual-Channel Deep Convolutional Neural Network. ...
doi:10.1109/tgrs.2020.2967201
fatcat:kpfxoidv5bgcfo36zfsnxe4aj4
Defect detection of seals in multilayer aseptic packages using deep learning
2019
Turkish Journal of Electrical Engineering and Computer Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Therefore, this study aims to perform a leak test in aseptic package seals by a system that makes decisions using independent deep learning methods. ...
The proposed Faster R-CNN and the Updated Faster R-CNN deep learning models were subjected to training and testing with a total of 400 images taken from a real production environment, resulting in a correct ...
Acknowledgment This work was supported by the Research Fund of the TÜBİTAK-TEYDEB, Project Number 2150314. ...
doi:10.3906/elk-1903-112
fatcat:aluqmsovajbzpoqgcesfclxwyy
Lasers that learn: The interface of laser machining and machine learning
2021
IET Optoelectronics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
However, recent breakthroughs in machine learning have resulted in neural networks that are capable of accurate and rapid modelling of laser machining at a scale, speed, and precision well beyond those ...
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. ...
Data supporting this study are openly available from the University of Southampton repository at https://doi.org/10.5258/ SOTON/D1710.
ORCID
Benjamin Mills https://orcid.org/0000-0002-1784-1012 ...
doi:10.1049/ote2.12039
fatcat:loc2t2l6end63k7sbpeubvys5u
Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy
2021
Healthcare
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Three-dimensional convolutional neural networks (3D CNN) of artificial intelligence (AI) are potent in image processing and recognition using deep learning to perform generative and descriptive tasks. ...
In conclusion, 3D CNN application can be a watershed moment in forensic medicine, leading to unprecedented improvement of forensic analysis workflows based on 3D neural networks. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/healthcare9111545
pmid:34828590
pmcid:PMC8619074
fatcat:wnexmx27gjfbjlri6tmy5rwkv4
Learning Neural Textual Representations for Citation Recommendation
2021
2020 25th International Conference on Pattern Recognition (ICPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Case Study on
Zero-Shot ASL Recognition
DAY 1 -Jan 12, 2021
Sharma, Renu; Ross, Arun
1677
Viability of Optical Coherence Tomography for Iris Presentation
Attack Detection
DAY 1 -Jan 12, 2021 ...
; Skocaj, Danijel 1532 End-To-End Training of a Two-Stage Neural Network for Defect Detection GAP: Quantifying the Generative Adversarial Set and Class Feature Applicability of Deep Neural Networks Deep ...
doi:10.1109/icpr48806.2021.9412725
fatcat:3vge2tpd2zf7jcv5btcixnaikm
Extraction and Analysis of Blue Steel Roofs Information Based on CNN Using Gaofen-2 Imageries
2020
Sensors
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Here, the DeeplabV3+ semantic segmentation neural network based on GaoFen-2 images was used to analyze the quantity and spatial distribution of blue steel roofs in the Nanhai district, Foshan (including ...
heat islands. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s20164655
pmid:32824822
fatcat:rpuqp5kupngaxndqmrt3svwuli
Overview of Memristor-Based Neural Network Design and Applications
2022
Frontiers in Physics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
deep neutral networks (DNNs) and spike neural networks (SNNs). ...
One of the most promising solutions to this issue is the development of an artificial neural network (ANN) that can process and store data in a manner similar to that of the human brain. ...
To address this problem, a deep-learning algorithm was developed for the perceptron based on a deep neural network (DNN). ...
doi:10.3389/fphy.2022.839243
fatcat:vd3tpopvrjd4la6eivu36b73aq
« Previous
Showing results 1 — 15 out of 836 results