Zobrazeno 1 - 10
of 82
pro vyhledávání: '"Mahantapas Kundu"'
Publikováno v:
Lecture Notes in Networks and Systems ISBN: 9789811951909
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd13c2869cb0c5e45ea7bc2bc09e59ae
https://doi.org/10.1007/978-981-19-5191-6_57
https://doi.org/10.1007/978-981-19-5191-6_57
Publikováno v:
Lecture Notes in Networks and Systems ISBN: 9789811951909
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c4f69f794c81f082408c59ca328aec7
https://doi.org/10.1007/978-981-19-5191-6_56
https://doi.org/10.1007/978-981-19-5191-6_56
Publikováno v:
Artificial Intelligence on Medical Data ISBN: 9789811901508
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27a688ebb671a91364515a669f8d5228
https://doi.org/10.1007/978-981-19-0151-5_12
https://doi.org/10.1007/978-981-19-0151-5_12
Autor:
Swarnendu Ghosh, Arpita Basak, Kalpita Dutta, Nibaran Das, Mita Nasipuri, Mahantapas Kundu, Malyaban Bal
Publikováno v:
Pattern Recognition Letters. 135:64-71
Encoder decoder models with multi-scale feature concatenations have become ubiquitous for various natural scene segmentation tasks. In the current approach, a similar model with an improved mirror connection from encoders to decoder has been proposed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b40f1919de5083af60dbfb174a4be8a
https://doi.org/10.1016/j.patrec.2020.04.002
https://doi.org/10.1016/j.patrec.2020.04.002
Publikováno v:
Neural Computing and Applications. 33:449-468
Recognition of unconstrained handwritten word images is an interesting research problem which gets more challenging when lexicon-free words are considered. Prerequisite for developing a lexicon-free handwritten word recognition technique is the segme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60379b0d2f5b2effc552ec5e8ece6b68
https://doi.org/10.1007/s00521-020-04981-w
https://doi.org/10.1007/s00521-020-04981-w
Publikováno v:
Communications in Computer and Information Science ISBN: 9783031113451
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91683fb18bff4e14c785339b944e3cd6
https://doi.org/10.1007/978-3-031-11346-8_40
https://doi.org/10.1007/978-3-031-11346-8_40
Publikováno v:
2021 IEEE 18th India Council International Conference (INDICON).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ae917e7ae37b1fa525d2f6efd84625f
https://doi.org/10.1109/indicon52576.2021.9691545
https://doi.org/10.1109/indicon52576.2021.9691545
Publikováno v:
Pattern Recognition Letters. 128:318-325
Identifying the most informative regions of character images is important for a robust handwritten character recognition system. If it is to be done in an efficient and cost-effective way, this task becomes more challenging. In this work, we have pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6faee20087c1627e136ef8c48080d8fd
https://doi.org/10.1016/j.patrec.2019.09.019
https://doi.org/10.1016/j.patrec.2019.09.019
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030755287
CICBA
CICBA
Multi-lingual script identification is a difficult task consisting of different language with complex backgrounds in scene text images. According to the current research scenario, deep neural networks are employed as teacher models to train a smaller
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::08a47db1b0bc6d34167e4b9501203521
https://doi.org/10.1007/978-3-030-75529-4_12
https://doi.org/10.1007/978-3-030-75529-4_12
Publikováno v:
Sensing and Imaging. 21
Finding local invariant patterns in handwritten characters and/or digits for optical character recognition is a difficult task. Variations in writing styles from one person to another make this task challenging. We have proposed a non-explicit featur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::605276ee2c4b7a9dd4451abd84bfacb1
https://doi.org/10.1007/s11220-020-00288-1
https://doi.org/10.1007/s11220-020-00288-1