Zobrazeno 1 - 10
of 7 233
pro vyhledávání: '"Sequeira P"'
Autor:
Sequeira, Ian, Barabas, Andrew Z., Barajas-Aguilar, Aaron H, Bacani, Michaela G, Nakatsuji, Naoto, Koshino, Mikito, Taniguichi, Takashi, Watanabe, Kenji, Sanchez-Yamagishi, Javier D.
Van der Waals (vdW) moires offer tunable superlattices that can strongly manipulate electronic properties. We demonstrate the in-situ manipulation of moire superlattices via heterostrain control in a vdW device. By straining a graphene layer relative
Externí odkaz:
http://arxiv.org/abs/2409.07427
Leveraging the capabilities of Knowledge Distillation (KD) strategies, we devise a strategy to fight the recent retraction of face recognition datasets. Given a pretrained Teacher model trained on a real dataset, we show that carefully utilising synt
Externí odkaz:
http://arxiv.org/abs/2408.17399
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
This study investigates the effects of occlusions on the fairness of face recognition systems, particularly focusing on demographic biases. Using the Racial Faces in the Wild (RFW) dataset and synthetically added realistic occlusions, we evaluate the
Externí odkaz:
http://arxiv.org/abs/2408.10175
Autor:
Gholipour, Hamed, Bozorgnia, Farid, Hambarde, Kailash, Mohammadigheymasi, Hamzeh, Mancilla, Javier, Sequeira, Andre, Neves, Joao, Proença, Hugo
Laplacian learning method is a well-established technique in classical graph-based semi-supervised learning, but its potential in the quantum domain remains largely unexplored. This study investigates the performance of the Laplacian-based Quantum Se
Externí odkaz:
http://arxiv.org/abs/2408.05498
This research explores the trainability of Parameterized Quantum circuit-based policies in Reinforcement Learning, an area that has recently seen a surge in empirical exploration. While some studies suggest improved sample complexity using quantum gr
Externí odkaz:
http://arxiv.org/abs/2406.09614
Range-based localization is ubiquitous: global navigation satellite systems (GNSS) power mobile phone-based navigation, and autonomous mobile robots can use range measurements from a variety of modalities including sonar, radar, and even WiFi signals
Externí odkaz:
http://arxiv.org/abs/2405.11550
Face recognition applications have grown in parallel with the size of datasets, complexity of deep learning models and computational power. However, while deep learning models evolve to become more capable and computational power keeps increasing, th
Externí odkaz:
http://arxiv.org/abs/2404.15234
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
Microbial assessment in a rare Norwegian book collection: a One Health approach to cultural heritage
Autor:
Sequeira, Sílvia O., Pasnak, Ekaterina, Viegas, Carla, Gomes, Bianca, Dias, Marta, Cervantes, Renata, Pena, Pedro, Twarużek, Magdalena, Kosicki, Robert, Viegas, Susana, Caetano, Liliana Aranha, Penetra, Maria João, Santos, Inês, Caldeira, Ana Teresa, Pinheiro, Catarina
Microbial contamination poses a threat to both the preservation of library and archival collections and the health of staff and users. This study investigated the microbial communities and potential health risks associated with the UNESCO-classified
Externí odkaz:
http://arxiv.org/abs/2404.00110