Ana Fred
researcher
Facts
8 properties- Instance of
- human
- Occupation
- researcher, computer scientist
- Educated at
- Instituto de Telecomunicações, Instituto de Telecomunicações, Instituto Superior Técnico[5]
- Doctoral advisor
- José M. N. Leitão[6]
🏷️ Also known as
en Ana Fred
en Ana L. N. Fred
🔖 Identifiers · 19
- ISNI
- 0000000116914657
- ORCID iD
- 0000-0003-1320-5024
- VIAF cluster ID
- 99344544
- Library of Congress Authorities ID
- nb2004304962
- GND ID
- 129313807
- CIÊNCIAVITAE ID
- 5F19-AD83-CE11
- DBLP author ID
- f/AnaLNFred
- DDB person (GND) ID
- 129313807
- Google Scholar author ID
- fMdRU1cAAAAJ
- IdRef ID
- 069218722
- J9U entity ID
- 987007330911105171
- MR Author ID
- 732618
Show all 19 identifiers +7
- Mathematics Genealogy Project ID
- 155390
- NUKAT ID
- n2006057621
- Nationale Thesaurus voor Auteursnamen ID
- 267772084
- Scopus author ID
- 6602080284
- Web of Science ResearcherID
- A-7464-2016
- WorldCat Entities ID
- E39PBJtrR3GwyQ93GYqMMbpdcP
- Yale LUX ID
- person/4e08a128-eb8a-4f81-863c-b6f87563b66f
🔗 Connections
Author of 23
A Low-Complexity R-peak Detection Algorithm with Adaptive Thresholding for Wearable Devices,
A novel approach to automatic seizure detection using computer vision and independent component analysis,
A real-world dataset of group emotion experiences based on physiological data,
A Review, Current Challenges, and Future Possibilities on Emotion Recognition Using Machine Learning and Physiological Signals,
Automatic Detection of a Phases for CAP Classification,
Automatic detection of cyclic alternating pattern,
Benchmarking of the BITalino biomedical toolkit against an established gold standard,
Biosignal-Based Multimodal Emotion Recognition in a Valence-Arousal Affective Framework Applied to Immersive Video Visualization
+15 more
← Authored by 23
A Low-Complexity R-peak Detection Algorithm with Adaptive Thresholding for Wearable Devices,
A novel approach to automatic seizure detection using computer vision and independent component analysis,
A real-world dataset of group emotion experiences based on physiological data,
A Review, Current Challenges, and Future Possibilities on Emotion Recognition Using Machine Learning and Physiological Signals,
Automatic Detection of a Phases for CAP Classification,
Automatic detection of cyclic alternating pattern,
Benchmarking of the BITalino biomedical toolkit against an established gold standard,
Biosignal-Based Multimodal Emotion Recognition in a Valence-Arousal Affective Framework Applied to Immersive Video Visualization
+15 more
Affiliated with 4
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