杠杆
发表于 2025-3-28 17:24:47
http://reply.papertrans.cn/29/2824/282314/282314_41.png
laxative
发表于 2025-3-28 20:36:46
http://reply.papertrans.cn/29/2824/282314/282314_42.png
cathartic
发表于 2025-3-29 02:43:35
https://doi.org/10.1007/978-3-319-89734-9fferent learning-free document analysis tasks. While machine learning is rather unexplored for graph representations, geometric deep learning offers a novel framework that allows for convolutional neural networks similar to the image domain. In this work, we show that the concept of attribute predic
馆长
发表于 2025-3-29 07:05:05
http://reply.papertrans.cn/29/2824/282314/282314_44.png
疏忽
发表于 2025-3-29 11:07:26
http://reply.papertrans.cn/29/2824/282314/282314_45.png
遗留之物
发表于 2025-3-29 14:29:38
http://reply.papertrans.cn/29/2824/282314/282314_46.png
不持续就爆
发表于 2025-3-29 19:04:54
http://reply.papertrans.cn/29/2824/282314/282314_47.png
Dysplasia
发表于 2025-3-29 22:11:56
https://doi.org/10.1007/978-981-10-8609-0 easily deployed in production and extended for further investigation. However, various factors like loosely organized codebases and sophisticated model configurations complicate the easy reuse of important innovations by a wide audience. Though there have been on-going efforts to improve reusabilit
evaculate
发表于 2025-3-29 23:59:45
https://doi.org/10.1007/978-94-007-2315-3ion is a common process in business workflows, there is a dire need of analyzing the potential of compressed models for the task of document image classification. Surprisingly, no such analysis has been done in the past. Furthermore, once a compressed model is obtained using a particular compression
cogitate
发表于 2025-3-30 04:42:48
http://reply.papertrans.cn/29/2824/282314/282314_50.png