Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Bhosale, Mahesh"'
Chart visualizations are essential for data interpretation and communication; however, most charts are only accessible in image format and lack the corresponding data tables and supplementary information, making it difficult to alter their appearance
Externí odkaz:
http://arxiv.org/abs/2403.00209
We propose a neural network architecture that learns body part appearances for soccer player re-identification. Our model consists of a two-stream network (one stream for appearance map extraction and the other for body part map extraction) and a bil
Externí odkaz:
http://arxiv.org/abs/2310.14469
Data extraction from line-chart images is an essential component of the automated document understanding process, as line charts are a ubiquitous data visualization format. However, the amount of visual and structural variations in multi-line graphs
Externí odkaz:
http://arxiv.org/abs/2305.01837
Publikováno v:
Analyst; 10/21/2023, Vol. 148 Issue 20, p4911-4921, 11p
Autor:
Phartale, Nagnath Nandu, Kadam, Tukaram Angadrao, Bhosale, Hemlata J., Karale, Mahesh A., Garimella, Gyananath
Publikováno v:
Journal of Basic & Applied Zoology; 5/7/2019, Vol. 80 Issue 1, pN.PAG-N.PAG, 1p
This six-volume set LNCS 14804-14809 constitutes the proceedings of the 18th International Conference on Document Analysis and Recognition, ICDAR 2024, held in Athens, Greece, during August 30–September 4, 2024. The total of 144 full papers present
This six-volume set of LNCS 14187, 14188, 14189, 14190, 14191 and 14192 constitutes the refereed proceedings of the 17th International Conference on Document Analysis and Recognition, ICDAR 2021, held in San José, CA, USA, in August 2023. The 53 f