A5077096463- Face recognition and analysis
- Face and Expression Recognition
- Neural dynamics and brain function
- Neural Networks and Applications
- Biometric Identification and Security
- Animal Vocal Communication and Behavior
- Evolutionary Algorithms and Applications
Tokyo University of the Arts
2022
The University of Tokyo
2022
This paper presents a summary of the Masked Face Recognition Competitions (MFR) held within 2021 International Joint Conference on Biometrics (IJCB 2021). The competition attracted total 10 participating teams with valid submissions. affiliations these are diverse and associated academia industry in nine different countries. These successfully submitted 18 solutions. is designed to motivate solutions aiming at enhancing face recognition accuracy masked faces. Moreover, considered...
Animals make efficient probabilistic inferences based on uncertain and noisy information from the outside environment. It is known that population codes, which have been proposed as a neural basis for encoding probability distributions, allow general networks (NNs) to perform near-optimal point estimation. However, mechanism of sampling-based inference has not clarified. In this study, we trained two types artificial NNs, feedforward NN (FFNN) recurrent (RNN), inference. Then analyzed...
This paper presents a summary of the Masked Face Recognition Competitions (MFR) held within 2021 International Joint Conference on Biometrics (IJCB 2021). The competition attracted total 10 participating teams with valid submissions. affiliations these are diverse and associated academia industry in nine different countries. These successfully submitted 18 solutions. is designed to motivate solutions aiming at enhancing face recognition accuracy masked faces. Moreover, considered...
Animals are known to make efficient probabilistic inferences based on uncertain and noisy information from the outside world. Although it is that generic neural networks can perform near-optimal point estimation by population codes which has been proposed as a basis for encoding of probability distribution, mechanisms sampling-based inference not clarified. In this study, we trained two types artificial networks: feedforward (FFNNs) recurrent (RNNs) sampling inference. Then, analyzed...