Zobrazeno 1 - 10
of 266 578
pro vyhledávání: '"Nascimento SO"'
The human-robot interaction (HRI) is a growing area of research. In HRI, complex command (action) classification is still an open problem that usually prevents the real applicability of such a technique. The literature presents some works that use ne
Externí odkaz:
http://arxiv.org/abs/2412.02863
In this work, we propose a minimalistic swarm flocking approach for multirotor unmanned aerial vehicles (UAVs). Our approach allows the swarm to achieve cohesively and aligned flocking (collective motion), in a random direction, without externally pr
Externí odkaz:
http://arxiv.org/abs/2412.02881
This paper addresses the problem of thrust estimation and control for the rotors of small-sized multirotors Uncrewed Aerial Vehicles (UAVs). Accurate control of the thrust generated by each rotor during flight is one of the main challenges for robust
Externí odkaz:
http://arxiv.org/abs/2412.02874
We obtain a class of solutions corresponding to a generalization of the Hayward black hole by solving the Einstein equations coupled to a particular nonlinear electromagnetic field. The generalization is realized by considering, additionally, the pre
Externí odkaz:
http://arxiv.org/abs/2412.00552
Clustering data using prior domain knowledge, starting from a partially labeled set, has recently been widely investigated. Often referred to as semi-supervised clustering, this approach leverages labeled data to enhance clustering accuracy. To maxim
Externí odkaz:
http://arxiv.org/abs/2411.14728
Autor:
Torres, Arthur Elwing, de Moura, Edleno Silva, da Silva, Altigran Soares, Nascimento, Mario A., Mesquita, Filipe
Named Entity Recognition (NER) is a machine learning task that traditionally relies on supervised learning and annotated data. Acquiring such data is often a challenge, particularly in specialized fields like medical, legal, and financial sectors. Th
Externí odkaz:
http://arxiv.org/abs/2411.14551
Autor:
Barros, Cauã Ferreira, Azevedo, Bruna Borges, Neto, Valdemar Vicente Graciano, Kassab, Mohamad, Kalinowski, Marcos, Nascimento, Hugo Alexandre D. do, Bandeira, Michelle C. G. S. P.
The exponential growth of text-based data in domains such as healthcare, education, and social sciences has outpaced the capacity of traditional qualitative analysis methods, which are time-intensive and prone to subjectivity. Large Language Models (
Externí odkaz:
http://arxiv.org/abs/2411.14473
Autor:
Nascimento, Nathalia, Guimaraes, Everton, Chintakunta, Sai Sanjna, Boominathan, Santhosh Anitha
The adoption of Large Language Models (LLMs) for code generation in data science offers substantial potential for enhancing tasks such as data manipulation, statistical analysis, and visualization. However, the effectiveness of these models in the da
Externí odkaz:
http://arxiv.org/abs/2411.11908
We calculate the mass renormalization for massive Dirac-like systems in (2+1)D due to the electron-phonon interaction at finite temperatures within the large-$N$ expansion. Our model combines the low-energy limit of charge carriers in a buckled honey
Externí odkaz:
http://arxiv.org/abs/2411.10621
In this work we define a class of injective-type norm on tensor products through the environment of sequence classes. Examples and results on this norm will be presented and the duality is studied in this context. As a byproduct, we present the defin
Externí odkaz:
http://arxiv.org/abs/2411.06938