Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Adnan Ul-Hasan"'
Autor:
Abdul Wahab, Muhammad Anas Tahir, Naveed Iqbal, Adnan Ul-Hasan, Faisal Shafait, Syed Muhammad Raza Kazmi
Publikováno v:
IEEE Access, Vol 9, Pp 96221-96232 (2021)
With the advent of smart grid, load forecasting is emerging as an essential technology to implement optimal planning and control of grid assets. Ergo in recent years, a significant thrust can be witnessed for the research towards the improvement of t
Externí odkaz:
https://doaj.org/article/3157486a57de48788cf0921253d4a4c6
Publikováno v:
International Journal on Document Analysis and Recognition (IJDAR). 25:373-384
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f6dd9aa5f471baaccd65c70c2e1ea7f
https://doi.org/10.1007/s10032-022-00416-5
https://doi.org/10.1007/s10032-022-00416-5
Publikováno v:
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c9f5d3752df88e79c15477ce36cc5f4
https://doi.org/10.1109/iceccme55909.2022.9988642
https://doi.org/10.1109/iceccme55909.2022.9988642
Publikováno v:
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76157950c57a45f8df061e7a7dd9b5b1
https://doi.org/10.1109/iceccme55909.2022.9987795
https://doi.org/10.1109/iceccme55909.2022.9987795
Autor:
Syed Muhammad Kumail Raza, Faisal Shafait, Muhammad Mubasher Khan, Adnan Ul-Hasan, Noor ul Sehr Zia, Muhammad Ferjad Naeem
Publikováno v:
Neural Computing and Applications. 34:1635-1648
An offline handwriting recognition system for Urdu, a language with a user base of 200 Million and written in Nastaleeq script, has been a challenge for the research community. The key problems include recognition of complex ligature shapes and lack
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::076b3496360dcadfe6f490338dcf726b
https://doi.org/10.1007/s00521-021-06498-2
https://doi.org/10.1007/s00521-021-06498-2
Autor:
Nauman Riaz, Haziq Arbab, Arooba Maqsood, Khuzaeymah Bin Nasir, Adnan Ul-Hasan, Faisal Shafait
Unconstrained off-line handwriting text recognition in general and for Arabic-like scripts in particular is a challenging task and is still an active researcharea. Transformer based models for English handwriting recognition have recently shown promi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ce688137fb905e251bfbe0198e368e3
https://doi.org/10.21203/rs.3.rs-1514700/v1
https://doi.org/10.21203/rs.3.rs-1514700/v1
Publikováno v:
Frontiers in Handwriting Recognition ISBN: 9783031216473
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::264bb4d6dbcc213cf6ee587becf963e0
https://doi.org/10.1007/978-3-031-21648-0_29
https://doi.org/10.1007/978-3-031-21648-0_29
Publikováno v:
Document Analysis Systems ISBN: 9783031065545
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35730f2484a0f345c0278b0cf315933f
https://doi.org/10.1007/978-3-031-06555-2_50
https://doi.org/10.1007/978-3-031-06555-2_50
Publikováno v:
2021 Digital Image Computing: Techniques and Applications (DICTA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c32d9efa8ed99567d3f7ab3c633047db
https://doi.org/10.1109/dicta52665.2021.9647245
https://doi.org/10.1109/dicta52665.2021.9647245
Publikováno v:
Document Analysis and Recognition – ICDAR 2021 ISBN: 9783030863302
ICDAR (2)
ICDAR (2)
Table Structure Recognition is an essential part of end-to-end tabular data extraction in document images. The recent success of deep learning model architectures in computer vision remains to be non-reflective in table structure recognition, largely
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1675d41fe819687a69d37b0ecf59992
https://doi.org/10.1007/978-3-030-86331-9_38
https://doi.org/10.1007/978-3-030-86331-9_38