Matches in SemOpenAlex for { <https://semopenalex.org/work/W2954680672> ?p ?o ?g. }
- W2954680672 endingPage "83796" @default.
- W2954680672 startingPage "83785" @default.
- W2954680672 abstract "Nowadays with the rapid development of technologies, machine vision has been used widely in various industries. The main applications of machine vision in industrial product lines are quality control (QC) and quality assurance (QA). The intelligent defects and anomalies recognition throughout the supply chain have come to be an integral part of quality control systems, in particular, in the food and pharmaceutical industries. In these industries, it is a legal requirement in manufacturing processes which can lead to minimizing the total number of defected products as well as maximizing the performance. In this paper, the machine vision has been utilized to monitor and control the proper packaging of drugs in pharmaceutical product lines. The main goal is counting the number of blister cards within a drug package. To tackle this problem, a new model based on object detection, feature extraction, and classification is proposed. Thanks to several strong approaches, such as the Haar cascade, HOG, ORG, Gabor wavelet, Radon transform, KNN, and SVM, and the accuracy over 88% is achieved in our experiments." @default.
- W2954680672 created "2019-07-12" @default.
- W2954680672 creator A5031542626 @default.
- W2954680672 creator A5050608316 @default.
- W2954680672 creator A5060900541 @default.
- W2954680672 date "2019-01-01" @default.
- W2954680672 modified "2023-10-16" @default.
- W2954680672 title "A Machine Learning-Based Approach for Counting Blister Cards Within Drug Packages" @default.
- W2954680672 cites W1103625893 @default.
- W2954680672 cites W1602291366 @default.
- W2954680672 cites W1665812053 @default.
- W2954680672 cites W1966299099 @default.
- W2954680672 cites W1971119598 @default.
- W2954680672 cites W1979360336 @default.
- W2954680672 cites W1982991855 @default.
- W2954680672 cites W1984199710 @default.
- W2954680672 cites W1985871455 @default.
- W2954680672 cites W1987828284 @default.
- W2954680672 cites W1988716939 @default.
- W2954680672 cites W1997636765 @default.
- W2954680672 cites W2017037483 @default.
- W2954680672 cites W2040719874 @default.
- W2954680672 cites W2063782155 @default.
- W2954680672 cites W2081865073 @default.
- W2954680672 cites W2104639174 @default.
- W2954680672 cites W2112702040 @default.
- W2954680672 cites W2120694107 @default.
- W2954680672 cites W2130931342 @default.
- W2954680672 cites W2132431872 @default.
- W2954680672 cites W2133763850 @default.
- W2954680672 cites W2135696199 @default.
- W2954680672 cites W2160547390 @default.
- W2954680672 cites W2179942681 @default.
- W2954680672 cites W2235800869 @default.
- W2954680672 cites W2313528501 @default.
- W2954680672 cites W2345524222 @default.
- W2954680672 cites W2394987826 @default.
- W2954680672 cites W2517141211 @default.
- W2954680672 cites W2520388804 @default.
- W2954680672 cites W2546677373 @default.
- W2954680672 cites W2549337046 @default.
- W2954680672 cites W2557032874 @default.
- W2954680672 cites W2565763730 @default.
- W2954680672 cites W2587540369 @default.
- W2954680672 cites W2598645336 @default.
- W2954680672 cites W2606436201 @default.
- W2954680672 cites W2613605632 @default.
- W2954680672 cites W2740588177 @default.
- W2954680672 cites W2748392996 @default.
- W2954680672 cites W2748912693 @default.
- W2954680672 cites W2762595912 @default.
- W2954680672 cites W2768160997 @default.
- W2954680672 cites W2772069281 @default.
- W2954680672 cites W2772666665 @default.
- W2954680672 cites W2783407418 @default.
- W2954680672 cites W2791729216 @default.
- W2954680672 cites W2794543249 @default.
- W2954680672 cites W2798280054 @default.
- W2954680672 cites W2804029648 @default.
- W2954680672 cites W2806990378 @default.
- W2954680672 cites W2839915472 @default.
- W2954680672 cites W2883839661 @default.
- W2954680672 cites W2886678544 @default.
- W2954680672 cites W2889026460 @default.
- W2954680672 cites W2894275155 @default.
- W2954680672 cites W2897817499 @default.
- W2954680672 cites W2900167835 @default.
- W2954680672 cites W3097096317 @default.
- W2954680672 doi "https://doi.org/10.1109/access.2019.2924445" @default.
- W2954680672 hasPublicationYear "2019" @default.
- W2954680672 type Work @default.
- W2954680672 sameAs 2954680672 @default.
- W2954680672 citedByCount "21" @default.
- W2954680672 countsByYear W29546806722019 @default.
- W2954680672 countsByYear W29546806722020 @default.
- W2954680672 countsByYear W29546806722021 @default.
- W2954680672 countsByYear W29546806722022 @default.
- W2954680672 countsByYear W29546806722023 @default.
- W2954680672 crossrefType "journal-article" @default.
- W2954680672 hasAuthorship W2954680672A5031542626 @default.
- W2954680672 hasAuthorship W2954680672A5050608316 @default.
- W2954680672 hasAuthorship W2954680672A5060900541 @default.
- W2954680672 hasBestOaLocation W29546806721 @default.
- W2954680672 hasConcept C106436119 @default.
- W2954680672 hasConcept C111472728 @default.
- W2954680672 hasConcept C119857082 @default.
- W2954680672 hasConcept C12267149 @default.
- W2954680672 hasConcept C127413603 @default.
- W2954680672 hasConcept C138885662 @default.
- W2954680672 hasConcept C153180895 @default.
- W2954680672 hasConcept C154945302 @default.
- W2954680672 hasConcept C21547014 @default.
- W2954680672 hasConcept C2524010 @default.
- W2954680672 hasConcept C2778618615 @default.
- W2954680672 hasConcept C2778938233 @default.
- W2954680672 hasConcept C2779530757 @default.
- W2954680672 hasConcept C33923547 @default.
- W2954680672 hasConcept C41008148 @default.