Search Results for author:
Found 7 papers, 1 papers with code
Novel entropy difference-based EEG channel selection technique for automated detection of ADHD
To verify the effectiveness of the channels selected, we explored three sets of features and classifiers.
CrowdFormer: Weakly-supervised Crowd counting with Improved Generalizability
However, due to their limited receptive field, CNNs fail to model the global context.
A Contactless Fingerprint Recognition System
The proposed system computes matching scores from CNN-based features and minutiae-based features.
Unsupervised Domain Adaptation for Cross-sensor Pore Detection in High-resolution Fingerprint Images
The core of the proposed approach for detection of pores in cross-sensor scenarios is DeepDomainPore, which is a residual learning-based convolutional neural network(CNN) trained for pore detection.
PoreNet: CNN-based Pore Descriptor for High-resolution Fingerprint Recognition
With the development of high-resolution fingerprint scanners, high-resolution fingerprint-based biometric recognition has received increasing attention in recent years.
PVSNet: Palm Vein Authentication Siamese Network Trained using Triplet Loss and Adaptive Hard Mining by Learning Enforced Domain Specific Features
Designing an end-to-end deep learning network to match the biometric features with limited training samples is an extremely challenging task.
Pore detection in high-resolution fingerprint images using Deep Residual Network
This letter presents a residual learning-based convolutional neural network, referred to as DeepResPore, for detection of pores in high-resolution fingerprint images.
