Zobrazeno 1 - 10
of 3 289
pro vyhledávání: '"Bonazzi, P."'
Autor:
Luca Bindi
Publikováno v:
Communications Earth & Environment, Vol 5, Iss 1, Pp 1-1 (2024)
Italian mineralogist Paola Bonazzi advanced our understanding of mineral structures and their environmental interactions. The mineral bonazziite, found in Kyrgyzstan, was named in honor of her seminal work on arsenic sulfides.
Externí odkaz:
https://doaj.org/article/b9eb263e89314e25926d89f0df6fb43d
Akademický článek
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Autor:
Bian, Sizhen, Kang, Pixi, Moosmann, Julian, Liu, Mengxi, Bonazzi, Pietro, Rosipal, Roman, Magno, Michele
Electroencephalogram (EEG)-based Brain-Computer Interfaces (BCIs) have garnered significant interest across various domains, including rehabilitation and robotics. Despite advancements in neural network-based EEG decoding, maintaining performance acr
Externí odkaz:
http://arxiv.org/abs/2409.00083
Autor:
Bonazzi, Francesco, Weikl, Thomas R.
Besides direct molecular interactions, proteins and nanoparticles embedded in or adsorbed to membranes experience indirect interactions that are mediated by the membranes. These membrane-mediated interactions arise from the membrane curvature induced
Externí odkaz:
http://arxiv.org/abs/2407.04027
Autor:
Bonazzi, Pietro, Wang, Mengqi, Arroyo, Diego Martin, Manhardt, Fabian, Messikomer, Nico, Tombari, Federico, Scaramuzza, Davide
Synthesizing realistic and diverse indoor 3D scene layouts in a controllable fashion opens up applications in simulated navigation and virtual reality. As concise and robust representations of a scene, scene graphs have proven to be well-suited as th
Externí odkaz:
http://arxiv.org/abs/2404.01887
Autor:
Bonazzi, Pietro, Rakatosaona, Marie-Julie, Cannici, Marco, Tombari, Federico, Scaramuzza, Davide
Existing deep learning methods for the reconstruction and denoising of point clouds rely on small datasets of 3D shapes. We circumvent the problem by leveraging deep learning methods trained on billions of images. We propose a method to reconstruct p
Externí odkaz:
http://arxiv.org/abs/2404.01112
Akademický článek
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Publikováno v:
Classica, Revista Brasileira de Estudos Clássicos, Vol 30, Iss 2, Pp 137-142 (2017)
Externí odkaz:
https://doaj.org/article/9a719ea4ef1e4707a59dfb8fbe8766ac
This paper addresses the growing interest in deploying deep learning models directly in-sensor. We present "Q-Segment", a quantized real-time segmentation algorithm, and conduct a comprehensive evaluation on a low-power edge vision platform with an i
Externí odkaz:
http://arxiv.org/abs/2312.09854
This paper introduces a neuromorphic methodology for eye tracking, harnessing pure event data captured by a Dynamic Vision Sensor (DVS) camera. The framework integrates a directly trained Spiking Neuron Network (SNN) regression model and leverages a
Externí odkaz:
http://arxiv.org/abs/2312.00425