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pro vyhledávání: '"Xue, Jintang"'
As a fundamental task in natural language processing, word embedding converts each word into a representation in a vector space. A challenge with word embedding is that as the vocabulary grows, the vector space's dimension increases and it can lead t
Externí odkaz:
http://arxiv.org/abs/2407.12342
Autor:
Yang, Yijing, Magoulianitis, Vasileios, Yang, Jiaxin, Xue, Jintang, Kaneko, Masatomo, Cacciamani, Giovanni, Abreu, Andre, Duddalwar, Vinay, Kuo, C. -C. Jay, Gill, Inderbir S., Nikias, Chrysostomos
Automatic prostate segmentation is an important step in computer-aided diagnosis of prostate cancer and treatment planning. Existing methods of prostate segmentation are based on deep learning models which have a large size and lack of transparency w
Externí odkaz:
http://arxiv.org/abs/2403.15971
Autor:
Magoulianitis, Vasileios, Yang, Jiaxin, Yang, Yijing, Xue, Jintang, Kaneko, Masatomo, Cacciamani, Giovanni, Abreu, Andre, Duddalwar, Vinay, Kuo, C. -C. Jay, Gill, Inderbir S., Nikias, Chrysostomos
Prostate Cancer is one of the most frequently occurring cancers in men, with a low survival rate if not early diagnosed. PI-RADS reading has a high false positive rate, thus increasing the diagnostic incurred costs and patient discomfort. Deep learni
Externí odkaz:
http://arxiv.org/abs/2403.15969
Chatbots have been studied for more than half a century. With the rapid development of natural language processing (NLP) technologies in recent years, chatbots using large language models (LLMs) have received much attention nowadays. Compared with tr
Externí odkaz:
http://arxiv.org/abs/2309.08836
As a specific category of artificial intelligence (AI), generative artificial intelligence (GenAI) generates new content that resembles what is created by humans. The rapid development of GenAI systems has created a huge amount of new data on the Int
Externí odkaz:
http://arxiv.org/abs/2306.17170
The design of a tiny machine learning model, which can be deployed in mobile and edge devices, for point cloud object classification is investigated in this work. To achieve this objective, we replace the multi-scale representation of a point cloud o
Externí odkaz:
http://arxiv.org/abs/2303.10898
Many point cloud classification methods are developed under the assumption that all point clouds in the dataset are well aligned with the canonical axes so that the 3D Cartesian point coordinates can be employed to learn features. When input point cl
Externí odkaz:
http://arxiv.org/abs/2302.11506
Autor:
Kaneko, Masatomo, Magoulianitis, Vasileios, Ramacciotti, Lorenzo Storino, Raman, Alex, Paralkar, Divyangi, Chen, Andrew, Chu, Timothy N., Yang, Yijing, Xue, Jintang, Yang, Jiaxin, Liu, Jinyuan, Jadvar, Donya S., Gill, Karanvir, Cacciamani, Giovanni E., Nikias, Chrysostomos L., Duddalwar, Vinay, Jay Kuo, C.-C., Gill, Inderbir S., Abreu, Andre Luis
Publikováno v:
In Urologic Clinics of North America February 2024 51(1):1-13
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