Zobrazeno 1 - 10
of 144
pro vyhledávání: '"Mandal, Bappaditya"'
Autor:
Shaw, Tarakeswar1, Mandal, Bappaditya1, Samanta, Gopinath2, Voigt, Thiemo3, Mitra, Debasis4, Augustine, Robin1 robin.augustine@angstrom.uu.se
Publikováno v:
Scientific Reports. 8/24/2024, Vol. 14 Issue 1, p1-16. 16p.
Autor:
Shaw, Tarakeswar, Mandal, Bappaditya, Mitra, Debasis, Rangaiah, Pramod K.B., Perez, Mauricio D., Augustine, Robin
Publikováno v:
In AEUE - International Journal of Electronics and Communications January 2024 173
Publikováno v:
In AEUE - International Journal of Electronics and Communications November 2023 171
This paper has been withdrawn by the authors due to insufficient or definition error(s) in the ethics approval protocol. Autism spectrum disorders (ASD) impact the cognitive, social, communicative and behavioral abilities of an individual. The develo
Externí odkaz:
http://arxiv.org/abs/1907.12537
Traditional machine learning algorithms using hand-crafted feature extraction techniques (such as local binary pattern) have limited accuracy because of high variation in images of the same class (or intra-class variation) for food recognition task.
Externí odkaz:
http://arxiv.org/abs/1812.10179
Among many biometrics such as face, iris, fingerprint and others, periocular region has the advantages over other biometrics because it is non-intrusive and serves as a balance between iris or eye region (very stringent, small area) and the whole fac
Externí odkaz:
http://arxiv.org/abs/1812.01465
Deep neural networks have recently achieved competitive accuracy for human activity recognition. However, there is room for improvement, especially in modeling long-term temporal importance and determining the activity relevance of different temporal
Externí odkaz:
http://arxiv.org/abs/1808.07272
Publikováno v:
In Signal Processing: Image Communication October 2022 108
In this work we propose a methodology for an automatic food classification system which recognizes the contents of the meal from the images of the food. We developed a multi-layered deep convolutional neural network (CNN) architecture that takes adva
Externí odkaz:
http://arxiv.org/abs/1709.09429
Smile is one of the key elements in identifying emotions and present state of mind of an individual. In this work, we propose a cluster of approaches to classify posed and spontaneous smiles using deep convolutional neural network (CNN) face features
Externí odkaz:
http://arxiv.org/abs/1701.01573