Zobrazeno 1 - 10
of 402
pro vyhledávání: '"Cardoso, Jaime S."'
As in school, one teacher to cover all subjects is insufficient to distill equally robust information to a student. Hence, each subject is taught by a highly specialised teacher. Following a similar philosophy, we propose a multiple specialized teach
Externí odkaz:
http://arxiv.org/abs/2408.16563
Algorithmic bias in healthcare mirrors existing data biases. However, the factors driving unfairness are not always known. Medical devices capture significant amounts of data but are prone to errors; for instance, pulse oximeters overestimate the art
Externí odkaz:
http://arxiv.org/abs/2408.04396
Semantic segmentation consists of predicting a semantic label for each image pixel. Conventional deep learning models do not take advantage of ordinal relations that might exist in the domain at hand. For example, it is known that the pupil is inside
Externí odkaz:
http://arxiv.org/abs/2407.20959
Manually annotating nuclei from the gigapixel Hematoxylin and Eosin (H&E)-stained Whole Slide Images (WSIs) is a laborious and costly task, meaning automated algorithms for cell nuclei instance segmentation and classification could alleviate the work
Externí odkaz:
http://arxiv.org/abs/2407.18673
Autor:
Gonçalves, Tiago, Pulido-Arias, Dagoberto, Willett, Julian, Hoebel, Katharina V., Cleveland, Mason, Ahmed, Syed Rakin, Gerstner, Elizabeth, Kalpathy-Cramer, Jayashree, Cardoso, Jaime S., Bridge, Christopher P., Kim, Albert E.
The interactions between tumor cells and the tumor microenvironment (TME) dictate therapeutic efficacy of radiation and many systemic therapies in breast cancer. However, to date, there is not a widely available method to reproducibly measure tumor a
Externí odkaz:
http://arxiv.org/abs/2404.16397
Autor:
DeAndres-Tame, Ivan, Tolosana, Ruben, Melzi, Pietro, Vera-Rodriguez, Ruben, Kim, Minchul, Rathgeb, Christian, Liu, Xiaoming, Morales, Aythami, Fierrez, Julian, Ortega-Garcia, Javier, Zhong, Zhizhou, Huang, Yuge, Mi, Yuxi, Ding, Shouhong, Zhou, Shuigeng, He, Shuai, Fu, Lingzhi, Cong, Heng, Zhang, Rongyu, Xiao, Zhihong, Smirnov, Evgeny, Pimenov, Anton, Grigorev, Aleksei, Timoshenko, Denis, Asfaw, Kaleb Mesfin, Low, Cheng Yaw, Liu, Hao, Wang, Chuyi, Zuo, Qing, He, Zhixiang, Shahreza, Hatef Otroshi, George, Anjith, Unnervik, Alexander, Rahimi, Parsa, Marcel, Sébastien, Neto, Pedro C., Huber, Marco, Kolf, Jan Niklas, Damer, Naser, Boutros, Fadi, Cardoso, Jaime S., Sequeira, Ana F., Atzori, Andrea, Fenu, Gianni, Marras, Mirko, Štruc, Vitomir, Yu, Jiang, Li, Zhangjie, Li, Jichun, Zhao, Weisong, Lei, Zhen, Zhu, Xiangyu, Zhang, Xiao-Yu, Biesseck, Bernardo, Vidal, Pedro, Coelho, Luiz, Granada, Roger, Menotti, David
Publikováno v:
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRw 2024)
Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class variability, time and errors produced in manual labeling, and in some c
Externí odkaz:
http://arxiv.org/abs/2404.10378
Autor:
Montenegro, Helena, Cardoso, Jaime S.
Case-based explanations are an intuitive method to gain insight into the decision-making process of deep learning models in clinical contexts. However, medical images cannot be shared as explanations due to privacy concerns. To address this problem,
Externí odkaz:
http://arxiv.org/abs/2311.04833
Autor:
Nakayama, Luis Filipe, Matos, João, Quion, Justin, Novaes, Frederico, Mitchell, William Greig, Mwavu, Rogers, Hung, Ju-Yi Ji, Santiago, Alvina Pauline dy, Phanphruk, Warachaya, Cardoso, Jaime S., Celi, Leo Anthony
Over the past two decades, exponential growth in data availability, computational power, and newly available modeling techniques has led to an expansion in interest, investment, and research in Artificial Intelligence (AI) applications. Ophthalmology
Externí odkaz:
http://arxiv.org/abs/2310.04997
With the ever-growing complexity of deep learning models for face recognition, it becomes hard to deploy these systems in real life. Researchers have two options: 1) use smaller models; 2) compress their current models. Since the usage of smaller mod
Externí odkaz:
http://arxiv.org/abs/2308.11840
Autor:
Caldeira, Eduarda, Neto, Pedro C., Gonçalves, Tiago, Damer, Naser, Sequeira, Ana F., Cardoso, Jaime S.
Morphing attacks keep threatening biometric systems, especially face recognition systems. Over time they have become simpler to perform and more realistic, as such, the usage of deep learning systems to detect these attacks has grown. At the same tim
Externí odkaz:
http://arxiv.org/abs/2306.03002