A5056072692- Spanish Linguistics and Language Studies
- Literacy and Educational Practices
- Educational Technology in Learning
- Second Language Learning and Teaching
- Cultural and Mythological Studies
- AI in cancer detection
- Immigration and Intercultural Education
- Image Retrieval and Classification Techniques
- Historical Linguistics and Language Studies
- Time Series Analysis and Forecasting
- EFL/ESL Teaching and Learning
- Image Processing Techniques and Applications
- Archaeological and Geological Studies
- Astronomy and Astrophysical Research
- Advanced Vision and Imaging
- Geography and Education Methods
- Colorectal Cancer Screening and Detection
- Advanced Image Processing Techniques
- Gender Studies in Language
- COVID-19 diagnosis using AI
- Educational Tools and Methods
- Higher Education Teaching and Evaluation
- Linguistic Variation and Morphology
- Blind Source Separation Techniques
- Digital literacy in education
Federico Santa María Technical University
2021
Pelican Cancer Foundation
2013
We present PiCam (Pelican Imaging Camera-Array), an ultra-thin high performance monolithic camera array, that captures light fields and synthesizes resolution images along with a range image (scene depth) through integrated parallax detection superresolution. The is passive, supporting both stills video, low capable, small enough to be included in the next generation of mobile devices including smartphones. Prior works [Rander et al. 1997; Yang 2002; Zhang Chen 2004; Tanida 2001; 2003;...
Medical imaging is essential nowadays throughout medical education, research, and care. Accordingly, international efforts have been made to set large-scale image repositories for these purposes. Yet, date, browsing of has troublesome, time-consuming, generally limited by text search engines. A paradigm shift, means a query-by-example engine, would alleviate constraints beneficially impact several practical demands the field. The current project aims address this gap in consumption...
Light curve analysis usually involves extracting manually designed features associated with physical parameters and visual inspection. The large amount of data collected nowadays in astronomy by different surveys represents a major challenge characterizing these signals. Therefore, finding good informative representation for them is key non-trivial task. Some studies have tried unsupervised machine learning approaches to generate this without much effectiveness. In article, we show that...