Zobrazeno 1 - 10
of 308
pro vyhledávání: '"Papa, João Paulo"'
Autor:
Paiola, Pedro Henrique, Garcia, Gabriel Lino, Manesco, João Renato Ribeiro, Roder, Mateus, Rodrigues, Douglas, Papa, João Paulo
This study evaluates the performance of large language models (LLMs) as medical agents in Portuguese, aiming to develop a reliable and relevant virtual assistant for healthcare professionals. The HealthCareMagic-100k-en and MedQuAD datasets, translat
Externí odkaz:
http://arxiv.org/abs/2410.00163
Autor:
Passos, Leandro A., Rodrigues, Douglas, Jodas, Danilo, Costa, Kelton A. P., Adeel, Ahsan, Papa, João Paulo
This paper presents BioNeRF, a biologically plausible architecture that models scenes in a 3D representation and synthesizes new views through radiance fields. Since NeRF relies on the network weights to store the scene's 3-dimensional representation
Externí odkaz:
http://arxiv.org/abs/2402.07310
Autor:
Garcia, Gabriel Lino, Paiola, Pedro Henrique, Morelli, Luis Henrique, Candido, Giovani, Júnior, Arnaldo Cândido, Jodas, Danilo Samuel, Afonso, Luis C. S., Guilherme, Ivan Rizzo, Penteado, Bruno Elias, Papa, João Paulo
Large Language Models (LLMs) are increasingly bringing advances to Natural Language Processing. However, low-resource languages, those lacking extensive prominence in datasets for various NLP tasks, or where existing datasets are not as substantial,
Externí odkaz:
http://arxiv.org/abs/2401.02909
Quality classification of wood boards is an essential task in the sawmill industry, which is still usually performed by human operators in small to median companies in developing countries. Machine learning algorithms have been successfully employed
Externí odkaz:
http://arxiv.org/abs/2310.13490
Autor:
Gomes, Nícolas Barbosa, Yoshida, Arissa, Roder, Mateus, de Oliveira, Guilherme Camargo, Papa, João Paulo
Identifying Amyotrophic Lateral Sclerosis (ALS) in its early stages is essential for establishing the beginning of treatment, enriching the outlook, and enhancing the overall well-being of those affected individuals. However, early diagnosis and dete
Externí odkaz:
http://arxiv.org/abs/2307.12159
Publikováno v:
Pattern Recognition 119 (2021): 108098
This work presents a thorough review concerning recent studies and text generation advancements using Generative Adversarial Networks. The usage of adversarial learning for text generation is promising as it provides alternatives to generate the so-c
Externí odkaz:
http://arxiv.org/abs/2212.11119
Automatic Text Summarization (ATS) is becoming relevant with the growth of textual data; however, with the popularization of public large-scale datasets, some recent machine learning approaches have focused on dense models and architectures that, des
Externí odkaz:
http://arxiv.org/abs/2212.10707
Machine Learning algorithms have been extensively researched throughout the last decade, leading to unprecedented advances in a broad range of applications, such as image classification and reconstruction, object recognition, and text categorization.
Externí odkaz:
http://arxiv.org/abs/2212.09447
Demands for minimum parameter setup in machine learning models are desirable to avoid time-consuming optimization processes. The $k$-Nearest Neighbors is one of the most effective and straightforward models employed in numerous problems. Despite its
Externí odkaz:
http://arxiv.org/abs/2209.12647
Despite the recent success of machine learning algorithms, most models face drawbacks when considering more complex tasks requiring interaction between different sources, such as multimodal input data and logical time sequences. On the other hand, th
Externí odkaz:
http://arxiv.org/abs/2206.02671