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A facial expression database is a collection of images or video clips with facial expressions of a range of emotions. Well-annotated ( emotion -tagged) media content of facial behavior is essential for training, testing, and validation of algorithms for the development of expression recognition systems .
Specialist abstracting and indexing database dedicated to public health research and practice. Contains scientific records from 1973 to the present. Subscription CABI: HCI Bibliography: Human–computer interface: An electronic bibliography for most of HCI for researchers, developers, educators, and students. Over 126,000 publications.
BioID Face Database Images of faces with eye positions marked. Manually set eye positions. 1521 Images, text Face recognition 2001 [94] [95] BioID Skin Segmentation Dataset Randomly sampled color values from face images. B, G, R, values extracted. 245,057 Text Segmentation, classification 2012 [96] [97] R. Bhatt. Bosphorus 3D Face image database.
Studierfenster (StudierFenster) is a free, non-commercial Open Science client/server-based Medical Imaging Processing (MIP) online framework. [52] Medical open network for AI is a framework for Deep learning in healthcare imaging that is open-source available under the Apache Licence and supported by the community. [53]
No (However, an open source is available.) 115+ major research institutions around the world, including the University of Cambridge (UK), University of Oxford (UK), University of Melbourne (AUS), Duke University (US), University of Auckland (NZ), Tufts University (US), and University of Michigan (US). (see Some of Symplectic's clients) UNIWeb
The Facial Recognition Technology (FERET) database is a dataset used for facial recognition system evaluation as part of the Face Recognition Technology (FERET) program.It was first established in 1993 under a collaborative effort between Harry Wechsler at George Mason University and Jonathon Phillips at the Army Research Laboratory in Adelphi, Maryland.
As a result of the FERET program, researchers were able to establish a common baseline for comparing different face-recognition algorithms and create a large standard database of facial images that is open for research. [1] In 2003, DARPA released a high-resolution, 24-bit color version of the images in the FERET database (existing reference).
MEDLINE (Medical Literature Analysis and Retrieval System Online, or MEDLARS Online) is a bibliographic database of life sciences and biomedical information. It includes bibliographic information for articles from academic journals covering medicine, nursing, pharmacy, dentistry, veterinary medicine, and health care.