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Face recognition systems are susceptible to presentation attacks such as printed photo attacks, replay attacks, and 3D mask attacks. These attacks, primarily studied in visible spectrum, aim to obfuscate or impersonate a person’s identity. This paper presents a unique multispectral video face database for face presentation attack using latex and paper masks. The proposed Multispectral Latex Mask based Video Face Presentation Attack (MLFP) database contains 1350 videos in visible, near infrared, and thermal spectrums. Since the database consists of videos of subjects without any mask as well as wearing ten different masks, the effect of identity concealment is analyzed in each spectrum using face recognition algorithms. We also present the performance of existing presentation attack detection algorithms on the proposed MLFP database. It is observed that the thermal imaging spectrum is most effective in detecting face presentation attacks.
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Assessing the synchronicity of anatoxinproducing benthic cyanobacteria and river ecosystem productivity
This was a conference presentation. The presentation included an overview about the benthic toxic mats, research objectives of this project and the modeling framework.
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- Award ID(s):
- 2222322
- PAR ID:
- 10569351
- Publisher / Repository:
- Society of Freshwater Science
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Liveness Detection (LivDet)-Face is an international competition series open to academia and industry. The competition’s objective is to assess and report state-of-the-art in liveness / Presentation Attack Detection (PAD) for face recognition. Impersonation and presentation of false samples to the sensors can be classified as presentation attacks and the ability for the sensors to detect such attempts is known as PAD. LivDet-Face 2021 * will be the first edition of the face liveness competition. This competition serves as an important benchmark in face presentation attack detection, offering (a) an independent assessment of the current state of the art in face PAD, and (b) a common evaluation protocol, availability of Presentation Attack Instruments (PAI) and live face image dataset through the Biometric Evaluation and Testing (BEAT) platform. The competition can be easily followed by researchers after it is closed, in a platform in which participants can compare their solutions against the LivDet-Face winners.more » « less
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Reliability and accuracy of iris biometric modality has prompted its large-scale deployment for critical applications such as border control and national ID projects. The extensive growth of iris recognition systems has raised apprehensions about susceptibility of these systems to various attacks. In the past, researchers have examined the impact of various iris presentation attacks such as textured contact lenses and print attacks. In this research, we present a novel presentation attack using deep learning based synthetic iris generation. Utilizing the generative capability of deep convolutional generative adversarial networks and iris quality metrics, we propose a new framework, named as iDCGAN (iris deep convolutional generative adversarial network) for generating realistic appearing synthetic iris images. We demonstrate the effect of these synthetically generated iris images as presentation attack on iris recognition by using a commercial system. The state-of-the-art presentation attack detection framework, DESIST is utilized to analyze if it can discriminate these synthetically generated iris images from real images. The experimental results illustrate that mitigating the proposed synthetic presentation attack is of paramount importance.more » « less
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Abstract Various signals in tissue microenvironments are often unevenly distributed around cells. Cellular responses to asymmetric cell‐matrix adhesion in a 3D space remain generally unclear and are to be studied at the single‐cell resolution. Here, the authors developed a droplet‐based microfluidic approach to manufacture a pure population of single cells in a microscale layer of compartmentalized 3D hydrogel matrices with a tunable spatial presentation of ligands at the subcellular level. Cells elongate with an asymmetric presentation of the integrin adhesion ligand Arg‐Gly‐Asp (RGD), while cells expand isotropically with a symmetric presentation of RGD. Membrane tension is higher on the side of single cells interacting with RGD than on the side without RGD. Finite element analysis shows that a non‐uniform isotropic cell volume expansion model is sufficient to recapitulate the experimental results. At a longer timescale, asymmetric ligand presentation commits mesenchymal stem cells to the osteogenic lineage. Cdc42 is an essential mediator of cell polarization and lineage specification in response to asymmetric cell‐matrix adhesion. This study highlights the utility of precisely controlling 3D ligand presentation around single cells to direct cell polarity for regenerative engineering and medicine.more » « less
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Accepted Manuscript1.0
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- The DOI is not currently available.
