AIMC Topic: Automated Facial Recognition

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Sparse Spatiotemporal Descriptor for Micro-Expression Recognition Using Enhanced Local Cube Binary Pattern.

Sensors (Basel, Switzerland)
As a spontaneous facial expression, a micro-expression can reveal the psychological responses of human beings. Thus, micro-expression recognition can be widely studied and applied for its potentiality in clinical diagnosis, psychological research, an...

MetalGAN: Multi-domain label-less image synthesis using cGANs and meta-learning.

Neural networks : the official journal of the International Neural Network Society
Image synthesis is currently one of the most addressed image processing topic in computer vision and deep learning fields of study. Researchers have tackled this problem focusing their efforts on its several challenging problems, e.g. image quality a...

Likelihood Ratios for Deep Neural Networks in Face Comparison.

Journal of forensic sciences
In this study, we aim to compare the performance of systems and forensic facial comparison experts in terms of likelihood ratio computation to assess the potential of the machine to support the human expert in the courtroom. In forensics, transparenc...

Who is the Winner? Memristive-CMOS Hybrid Modules: CNN-LSTM Versus HTM.

IEEE transactions on biomedical circuits and systems
Hierarchical, modular and sparse information processing are signature characteristics of biological neural networks. These aspects have been the backbone of several artificial neural network designs of the brain-like networks, including Hierarchical ...

Neural Probabilistic Graphical Model for Face Sketch Synthesis.

IEEE transactions on neural networks and learning systems
Neural network learning for face sketch synthesis from photos has attracted substantial attention due to its favorable synthesis performance. However, most existing deep-learning-based face sketch synthesis models stacked only by multiple convolution...

Label-less Learning for Emotion Cognition.

IEEE transactions on neural networks and learning systems
In this paper, we propose a label-less learning for emotion cognition (LLEC) to achieve the utilization of a large amount of unlabeled data. We first inspect the unlabeled data from two perspectives, i.e., the feature layer and the decision layer. By...

Deep Spiking Neural Network for Video-Based Disguise Face Recognition Based on Dynamic Facial Movements.

IEEE transactions on neural networks and learning systems
With the increasing popularity of social media and smart devices, the face as one of the key biometrics becomes vital for person identification. Among those face recognition algorithms, video-based face recognition methods could make use of both temp...

Online Incremental Classification Resonance Network and Its Application to Human-Robot Interaction.

IEEE transactions on neural networks and learning systems
In human-robot interaction (HRI), classification is one of the most important problems, and it is essential particularly when the robot recognizes the surroundings and chooses a reaction based on a certain situation. Each interaction is different sin...

Robust RGB-D Face Recognition Using Attribute-Aware Loss.

IEEE transactions on pattern analysis and machine intelligence
Existing convolutional neural network (CNN) based face recognition algorithms typically learn a discriminative feature mapping, using a loss function that enforces separation of features from different classes and/or aggregation of features within th...

Face-from-Depth for Head Pose Estimation on Depth Images.

IEEE transactions on pattern analysis and machine intelligence
Depth cameras allow to set up reliable solutions for people monitoring and behavior understanding, especially when unstable or poor illumination conditions make unusable common RGB sensors. Therefore, we propose a complete framework for the estimatio...