AIMC Topic: Biometric Identification
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Cross-Generation Kinship Verification with Sparse Discriminative Metric.
IEEE transactions on pattern analysis and machine intelligence
Aug 1, 2018
Kinship verification is a very important technique in many real-world applications, e.g., personal album organization, missing person investigation and forensic analysis. However, it is extremely difficult to verify a family pair with generation gap,...
3D-Aided Dual-Agent GANs for Unconstrained Face Recognition.
IEEE transactions on pattern analysis and machine intelligence
Jul 23, 2018
Synthesizing realistic profile faces is beneficial for more efficiently training deep pose-invariant models for large-scale unconstrained face recognition, by augmenting the number of samples with extreme poses and avoiding costly annotation work. Ho...
An end to end Deep Neural Network for iris segmentation in unconstrained scenarios.
Neural networks : the official journal of the International Neural Network Society
Jun 30, 2018
With the increasing imaging and processing capabilities of today's mobile devices, user authentication using iris biometrics has become feasible. However, as the acquisition conditions become more unconstrained and as image quality is typically lower...
EEG-Based Biometrics: Challenges And Applications.
Computational intelligence and neuroscience
Jun 7, 2018
Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition.
IEEE transactions on pattern analysis and machine intelligence
Jun 1, 2018
Heterogeneous face recognition (HFR) aims at matching facial images acquired from different sensing modalities with mission-critical applications in forensics, security and commercial sectors. However, HFR presents more challenging issues than tradit...
Nonlinear analysis and synthesis of video images using deep dynamic bottleneck neural networks for face recognition.
Neural networks : the official journal of the International Neural Network Society
May 31, 2018
Nonlinear components extracted from deep structures of bottleneck neural networks exhibit a great ability to express input space in a low-dimensional manifold. Sharing and combining the components boost the capability of the neural networks to synthe...
An Improved Multispectral Palmprint Recognition System Using Autoencoder with Regularized Extreme Learning Machine.
Computational intelligence and neuroscience
May 27, 2018
Multispectral palmprint recognition system (MPRS) is an essential technology for effective human identification and verification tasks. To improve the accuracy and performance of MPRS, a novel approach based on autoencoder (AE) and regularized extrem...
On the Reconstruction of Face Images from Deep Face Templates.
IEEE transactions on pattern analysis and machine intelligence
Apr 16, 2018
State-of-the-art face recognition systems are based on deep (convolutional) neural networks. Therefore, it is imperative to determine to what extent face templates derived from deep networks can be inverted to obtain the original face image. In this ...
A critical review on the use of artificial neural networks in olive oil production, characterization and authentication.
Critical reviews in food science and nutrition
Feb 16, 2018
Artificial neural networks (ANN) are computationally based mathematical tools inspired by the fundamental cell of the nervous system, the neuron. ANN constitute a simplified artificial replica of the human brain consisting of parallel processing neur...
Analysis of Spatio-Temporal Representations for Robust Footstep Recognition with Deep Residual Neural Networks.
IEEE transactions on pattern analysis and machine intelligence
Jan 30, 2018
Human footsteps can provide a unique behavioural pattern for robust biometric systems. We propose spatio-temporal footstep representations from floor-only sensor data in advanced computational models for automatic biometric verification. Our models d...
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