Zobrazeno 1 - 10
of 142
pro vyhledávání: '"Chiang, Yao-Yi"'
Publikováno v:
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'24). Singapore: Springer Nature Singapore, 2024
Diagnosing epilepsy requires accurate seizure detection and classification, but traditional manual EEG signal analysis is resource-intensive. Meanwhile, automated algorithms often overlook EEG's geometric and semantic properties critical for interpre
Externí odkaz:
http://arxiv.org/abs/2405.09568
Humans subconsciously engage in geospatial reasoning when reading articles. We recognize place names and their spatial relations in text and mentally associate them with their physical locations on Earth. Although pretrained language models can mimic
Externí odkaz:
http://arxiv.org/abs/2310.14478
Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors’ Data
Autor:
Li, Kenan, Habre, Rima, Deng, Huiyu, Urman, Robert, Morrison, John, Gilliland, Frank D, Ambite, José Luis, Stripelis, Dimitris, Chiang, Yao-Yi, Lin, Yijun, Bui, Alex AT, King, Christine, Hosseini, Anahita, Vliet, Eleanne Van, Sarrafzadeh, Majid, Eckel, Sandrah P
Publikováno v:
JMIR mHealth and uHealth, Vol 7, Iss 2, p e11201 (2019)
BackgroundTime-resolved quantification of physical activity can contribute to both personalized medicine and epidemiological research studies, for example, managing and identifying triggers of asthma exacerbations. A growing number of reportedly accu
Externí odkaz:
https://doaj.org/article/a47035c922a94672a72ed6632c7de107
Scanned historical maps in libraries and archives are valuable repositories of geographic data that often do not exist elsewhere. Despite the potential of machine learning tools like the Google Vision APIs for automatically transcribing text from the
Externí odkaz:
http://arxiv.org/abs/2306.17059
Autor:
Hajisafi, Arash, Lin, Haowen, Shaham, Sina, Hu, Haoji, Siampou, Maria Despoina, Chiang, Yao-Yi, Shahabi, Cyrus
Forecasting the number of visits to Points-of-Interest (POI) in an urban area is critical for planning and decision-making for various application domains, from urban planning and transportation management to public health and social studies. Althoug
Externí odkaz:
http://arxiv.org/abs/2306.15927
Autor:
Yin, Xiaozhe, Fallah-Shorshani, Masoud, McConnell, Rob, Fruin, Scott, Chiang, Yao-Yi, Franklin, Meredith
As the availability, size and complexity of data have increased in recent years, machine learning (ML) techniques have become popular for modeling. Predictions resulting from applying ML models are often used for inference, decision-making, and downs
Externí odkaz:
http://arxiv.org/abs/2304.11732
Human mobility clustering is an important problem for understanding human mobility behaviors (e.g., work and school commutes). Existing methods typically contain two steps: choosing or learning a mobility representation and applying a clustering algo
Externí odkaz:
http://arxiv.org/abs/2301.08524
Named geographic entities (geo-entities for short) are the building blocks of many geographic datasets. Characterizing geo-entities is integral to various application domains, such as geo-intelligence and map comprehension, while a key challenge is t
Externí odkaz:
http://arxiv.org/abs/2210.12213
Transportation infrastructure, such as road or railroad networks, represent a fundamental component of our civilization. For sustainable planning and informed decision making, a thorough understanding of the long-term evolution of transportation infr
Externí odkaz:
http://arxiv.org/abs/2202.04883