Zobrazeno 1 - 10
of 2 325
pro vyhledávání: '"P. Ngu"'
Autor:
Lee, Nathaniel, Ngu, Noel, Sahdev, Harshdeep Singh, Motaganahall, Pramod, Chowdhury, Al Mehdi Saadat, Xi, Bowen, Shakarian, Paulo
Predicting price spikes in critical metals such as Cobalt, Copper, Magnesium, and Nickel is crucial for mitigating economic risks associated with global trends like the energy transition and reshoring of manufacturing. While traditional models have f
Externí odkaz:
http://arxiv.org/abs/2410.12785
This article presents the Labeled Random Finite Set (LRFS) framework for multi-object systems-systems in which the number of objects and their states are unknown and vary randomly with time. In particular, we focus on state and trajectory estimation
Externí odkaz:
http://arxiv.org/abs/2409.18531
We propose a 3D multi-object tracking (MOT) solution using only 2D detections from monocular cameras, which automatically initiates/terminates tracks as well as resolves track appearance-reappearance and occlusions. Moreover, this approach does not r
Externí odkaz:
http://arxiv.org/abs/2405.18606
The combination of increased life expectancy and falling birth rates is resulting in an aging population. Wearable Sensor-based Human Activity Recognition (WSHAR) emerges as a promising assistive technology to support the daily lives of older individ
Externí odkaz:
http://arxiv.org/abs/2404.15349
Autor:
Nguyen, Le Ngu, Casado, Constantino Álvarez, Cañellas, Manuel Lage, Mukherjee, Anirban, Nguyen, Nhi, Jayagopi, Dinesh Babu, López, Miguel Bordallo
Radio frequency (RF) signals have facilitated the development of non-contact human monitoring tasks, such as vital signs measurement, activity recognition, and user identification. In some specific scenarios, an RF signal analysis framework may prior
Externí odkaz:
http://arxiv.org/abs/2401.05538
Autor:
Nguyen, Le Ngu, Susarla, Praneeth, Mukherjee, Anirban, Cañellas, Manuel Lage, Casado, Constantino Álvarez, Wu, Xiaoting, Olli~Silvén, Jayagopi, Dinesh Babu, López, Miguel Bordallo
Indoor human monitoring systems leverage a wide range of sensors, including cameras, radio devices, and inertial measurement units, to collect extensive data from users and the environment. These sensors contribute diverse data modalities, such as vi
Externí odkaz:
http://arxiv.org/abs/2312.07601
Error prediction in large language models often relies on domain-specific information. In this paper, we present measures for quantification of error in the response of a large language model based on the diversity of responses to a given prompt - he
Externí odkaz:
http://arxiv.org/abs/2308.11189
Wearable sensor-based Human Action Recognition (HAR) has made significant strides in recent times. However, the accuracy performance of wearable sensor-based HAR is currently still lagging behind that of visual modalities-based systems, such as RGB v
Externí odkaz:
http://arxiv.org/abs/2307.03638
Publikováno v:
AAAI Spring Symposium 2023 (MAKE)
We study the performance of a commercially available large language model (LLM) known as ChatGPT on math word problems (MWPs) from the dataset DRAW-1K. To our knowledge, this is the first independent evaluation of ChatGPT. We found that ChatGPT's per
Externí odkaz:
http://arxiv.org/abs/2302.13814
Autor:
Haghighi, Fatemeh, Ghosh, Soumitra, Ngu, Hai, Chu, Sarah, Lin, Han, Hejrati, Mohsen, Bingol, Baris, Hashemifar, Somaye
Parkinson's Disease (PD) is the second most common neurodegenerative disease in humans. PD is characterized by the gradual loss of dopaminergic neurons in the Substantia Nigra (SN). Counting the number of dopaminergic neurons in the SN is one of the
Externí odkaz:
http://arxiv.org/abs/2301.08141