Zobrazeno 1 - 10
of 1 504
pro vyhledávání: '"Ortiz, Jorge A."'
In current multimodal tasks, models typically freeze the encoder and decoder while adapting intermediate layers to task-specific goals, such as region captioning. Region-level visual understanding presents significant challenges for large-scale visio
Externí odkaz:
http://arxiv.org/abs/2412.10348
Autor:
Pargoo, Navid Salami, Ghasemi, Mahshid, Xia, Shuren, Turkcan, Mehmet Kerem, Ehsan, Taqiya, Zang, Chengbo, Sun, Yuan, Ghaderi, Javad, Zussman, Gil, Kostic, Zoran, Ortiz, Jorge
As urban populations grow, cities are becoming more complex, driving the deployment of interconnected sensing systems to realize the vision of smart cities. These systems aim to improve safety, mobility, and quality of life through applications that
Externí odkaz:
http://arxiv.org/abs/2411.19714
Autor:
Muslimov, Eduard, Castillo-Dominguez, Edgar, Kariuki, James, Chao-Ortiz, Jorge, Tecza, Matthias, Meyer, Elliot, Ozer, Zeynep, Clarke, Fraser, Thatte, Niranjan
Publikováno v:
Proc. SPIE 13096, 130964W (2024)
HARMONI is the first light visible and near-IR integral field spectrograph for the ELT. It covers a large spectral range from 470nm to 2450nm with resolving powers from 3300 to 18000 and spatial sampling from 60mas to 4mas. It can operate in two Adap
Externí odkaz:
http://arxiv.org/abs/2410.01581
Complex human activity recognition (CHAR) remains a pivotal challenge within ubiquitous computing, especially in the context of smart environments. Existing studies typically require meticulous labeling of both atomic and complex activities, a task t
Externí odkaz:
http://arxiv.org/abs/2407.03291
Autor:
Sun, Yuan, Ortiz, Jorge
Complex activity recognition plays an important role in elderly care assistance. However, the reasoning ability of edge devices is constrained by the classic machine learning model capacity. In this paper, we present a non-invasive ambient sensing sy
Externí odkaz:
http://arxiv.org/abs/2407.02606
Autor:
Sun, Yuan, Ortiz, Jorge
With the continuous advancement of technology, artificial intelligence has significantly impacted various fields, particularly healthcare. Generative models, a key AI technology, have revolutionized medical image generation, data analysis, and diagno
Externí odkaz:
http://arxiv.org/abs/2406.06627
Reinforcement Learning from Human Feedback (RLHF) is popular in large language models (LLMs), whereas traditional Reinforcement Learning (RL) often falls short. Current autonomous driving methods typically utilize either human feedback in machine lea
Externí odkaz:
http://arxiv.org/abs/2406.04481
Designing a User-centric Framework for Information Quality Ranking of Large-scale Street View Images
Street view imagery (SVI), largely captured via outfitted fleets or mounted dashcams in consumer vehicles is a rapidly growing source of geospatial data used in urban sensing and development. These datasets are often collected opportunistically, are
Externí odkaz:
http://arxiv.org/abs/2404.00392
Autor:
Bremers, Alexandra, Friedman, Natalie, Lee, Sam, Wu, Tong, Laurier, Eric, Jung, Malte, Ortiz, Jorge, Ju, Wendy
Unpleasant social interactions on the road can negatively affect driving safety. At the same time, researchers have attempted to address social discomfort by exploring Conversational User Interfaces (CUIs) as social mediators. Before knowing whether
Externí odkaz:
http://arxiv.org/abs/2311.04456
Autor:
Tellez, Felipe, Ortiz, Jorge
Publikováno v:
Int. J. Adv. Comput. Sci. Appl. (IJACSA), Vol. 15, No. 6, 2024, pp. 1539-1553
This paper presents a comparative analysis between the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), two vital artificial intelligence algorithms, focusing on optimizing Elliptic Curve Cryptography (ECC) parameters. These encompass th
Externí odkaz:
http://arxiv.org/abs/2310.06752