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Full-Text Articles in Electrical and Computer Engineering
Multimodal Adversarial Learning, Uche Osahor
Multimodal Adversarial Learning, Uche Osahor
Graduate Theses, Dissertations, and Problem Reports
Deep Convolutional Neural Networks (DCNN) have proven to be an exceptional tool for object recognition, generative modelling, and multi-modal learning in various computer vision applications. However, recent findings have shown that such state-of-the-art models can be easily deceived by inserting slight imperceptible perturbations to key pixels in the input. A good target detection systems can accurately identify targets by localizing their coordinates on the input image of interest. This is ideally achieved by labeling each pixel in an image as a background or a potential target pixel. However, prior research still confirms that such state of the art targets models …
Landmark Enforcement And Principal Component Analysis For Improving Gan-Based Morphing, Samuel W. Price
Landmark Enforcement And Principal Component Analysis For Improving Gan-Based Morphing, Samuel W. Price
Graduate Theses, Dissertations, and Problem Reports
Facial Recognition Systems (FRSs) are a key target for adversaries determined to circumvent security checkpoints. Morph images threaten FRS by presenting as multiple individuals, allowing an adversary to swap identities with another subject. Although morph generation using generative adversarial networks (GANs) results in high-quality morphs without possessing the spatial artifacts caused by landmarkbased methods, there is an apparent loss in identity with standard GAN-based morphing methods. In this thesis, we examine landmark-based and GAN-based morphing methods to fuse the advantages of both methodologies. We propose a novel StyleGAN2 morph generation technique by introducing a landmark enforcement method. Considering this method, …
Integration Of Deep Hashing And Channel Coding For Biometric Security And Biometric Retrieval, Veeru Talreja
Integration Of Deep Hashing And Channel Coding For Biometric Security And Biometric Retrieval, Veeru Talreja
Graduate Theses, Dissertations, and Problem Reports
In the last few years, the research growth in many research and commercial fields are due to the adoption of state of the art deep learning techniques. The same applies to even biometrics and biometric security. Additionally, there has been a rise in the development of deep learning techniques used for approximate nearest neighbor (ANN) search for retrieval on multi-modal datasets. These deep learning techniques knows as deep hashing (DH) integrate feature learning and hash coding into an end-to-end trainable framework. Motivated by these factors, this dissertation considers the integration of deep hashing and channel coding for biometric security and …
Palmprint Gender Classification Using Deep Learning Methods, Minou Khayami
Palmprint Gender Classification Using Deep Learning Methods, Minou Khayami
Graduate Theses, Dissertations, and Problem Reports
Gender identification is an important technique that can improve the performance of authentication systems by reducing searching space and speeding up the matching process. Several biometric traits have been used to ascertain human gender. Among them, the human palmprint possesses several discriminating features such as principal-lines, wrinkles, ridges, and minutiae features and that offer cues for gender identification. The goal of this work is to develop novel deep-learning techniques to determine gender from palmprint images. PolyU and CASIA palmprint databases with 90,000 and 5502 images respectively were used for training and testing purposes in this research. After ROI extraction and …