A comprehensive overview of feature representation for biometric recognition
I Rida, N Al-Maadeed, S Al-Maadeed… - Multimedia Tools and …, 2020 - Springer
The performance of any biometric recognition system heavily dependents on finding a good
and suitable feature representation space where observations from different classes are well …
and suitable feature representation space where observations from different classes are well …
[HTML][HTML] A survey on minutiae-based palmprint feature representations, and a full analysis of palmprint feature representation role in latent identification performance
Latent palmprint identification is a crucial element for both law enforcement and integrated
automated fingerprint identification systems because approximately 30% of the imprints …
automated fingerprint identification systems because approximately 30% of the imprints …
An efficient feature selection and explainable classification method for EEG-based epileptic seizure detection
Epilepsy is a prevalent neurological disorder that poses life-threatening emergencies. Early
electroencephalogram (EEG) seizure detection can mitigate the risks and aid in the …
electroencephalogram (EEG) seizure detection can mitigate the risks and aid in the …
Palmprint recognition with an efficient data driven ensemble classifier
Palmprint recognition is an important and widely used modality in biometric systems. It has a
high reliability, stability and user acceptability. This paper proposes a new and effective …
high reliability, stability and user acceptability. This paper proposes a new and effective …
Palmprint identification using an ensemble of sparse representations
Among various palmprint identification methods proposed in the literature, sparse
representation for classification (SRC) is very attractive offering high accuracy. Although …
representation for classification (SRC) is very attractive offering high accuracy. Although …
The encoding method of position embeddings in vision transformer
K Jiang, P Peng, Y Lian, W Xu - Journal of Visual Communication and …, 2022 - Elsevier
Abstract In contrast to Convolutional Neural Networks (CNNs), Vision Transformers (ViT)
cannot capture sequence ordering of input tokens and require position embeddings. As a …
cannot capture sequence ordering of input tokens and require position embeddings. As a …
[HTML][HTML] Energy-efficient Gabor kernels in neural networks with genetic algorithm training method
F Meng, X Wang, F Shao, D Wang, X Hua - Electronics, 2019 - mdpi.com
Deep-learning convolutional neural networks (CNNs) have proven to be successful in
various cognitive applications with a multilayer structure. The high computational energy …
various cognitive applications with a multilayer structure. The high computational energy …
Palmprint identification using sparse and dense hybrid representation
Among various palmprint identification methods proposed in the literature, Sparse
Representation for Classification (SRC) is very attractive, offering high accuracy. Although …
Representation for Classification (SRC) is very attractive, offering high accuracy. Although …
Towards human body-part learning for model-free gait recognition
I Rida - arXiv preprint arXiv:1904.01620, 2019 - arxiv.org
Gait based biometric aims to discriminate among people by the way or manner they walk. It
represents a biometric at distance which has many advantages over other biometric …
represents a biometric at distance which has many advantages over other biometric …
Forensic shoe-print identification: a brief survey
As an advanced research topic in forensics science, automatic shoe-print identification has
been extensively studied in the last two decades, since shoe marks are the clues most …
been extensively studied in the last two decades, since shoe marks are the clues most …