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- Channel Coding (1)
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- Data Augmentation (1)
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- Face Detection (1)
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Articles 1 - 5 of 5
Full-Text Articles in Electrical and Computer Engineering
Interoperability Of Contact And Contactless Fingerprints Across Multiple Fingerprint Sensors, Brady M. Williams
Interoperability Of Contact And Contactless Fingerprints Across Multiple Fingerprint Sensors, Brady M. Williams
Graduate Theses, Dissertations, and Problem Reports
Contactless fingerprinting devices have grown in popularity in recent years due to speed and convenience of capture. Also, due to the global COID-19 pandemic, the need for safe and hygienic options for fingerprint capture are more pressing than ever. However, contactless systems face challenges in the areas of interoperability and matching performance as shown in other works. In this paper, we present a contactless vs. contact interoperability assessment of several contactless devices, including cellphone fingerphoto capture. During the interoperability assessment, the quality of the fingerprints was considered using the NBIS NFIQ software with the contact-based fingerprint performing the best overall …
Identical Twins As A Facial Similarity Benchmark For Human Facial Recognition, John Andrew Mccauley
Identical Twins As A Facial Similarity Benchmark For Human Facial Recognition, John Andrew Mccauley
Graduate Theses, Dissertations, and Problem Reports
The problem of distinguishing identical twins and non-twin look-alikes in automated facial recognition (FR) applications has become increasingly important with the widespread adoption of facial biometrics. Due to the high facial similarity of both identical twins and look-alikes, these face pairs represent the hardest cases presented to facial recognition tools. This work presents an application of one of the largest twin datasets compiled to date to address two FR challenges: 1) determining a baseline measure of facial similarity between identical twins and 2) applying this similarity measure to determine the impact of doppelgangers, or look-alikes, on FR performance for large …
Weed Recognition In Agriculture: A Mask R-Cnn Approach, Sruthi Keerthi Valicharla
Weed Recognition In Agriculture: A Mask R-Cnn Approach, Sruthi Keerthi Valicharla
Graduate Theses, Dissertations, and Problem Reports
Recent interdisciplinary collaboration on deep learning has led to a growing interest in its application in the agriculture domain. Weed control and management are some of the crucial tasks in agriculture to maintain high crop productivity. The inception phase of weed control and management is to successfully recognize the weed plants, followed by providing a suitable management plan. Due to the complexities in agriculture images, such as similar colour and texture, we need to incorporate a deep neural network that uses pixel-wise grouping for identifying the plant species. In this thesis, we analysed the performance of one of the most …
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 …
An End-To-End Face Recognition System Evaluation Framework, James Andrew Duncan
An End-To-End Face Recognition System Evaluation Framework, James Andrew Duncan
Graduate Theses, Dissertations, and Problem Reports
The performance of face recognition system components is traditionally reported using metrics such as the Receiver Operating Characteristic (ROC), Cumulative Match Characteristic (CMC), and Identification Error Tradeoff (IET). Recently, new metrics have been published to take advantage of annotation-dense datasets such as IARPA Janus Benchmark-Surveillance and IARPA Janus Benchmark-Multi Domain Face to describe end-to-end face recognition system performance. Unlike traditional (component-level) analysis, end-to-end analysis of a system produces a metric proportional to the experience of a user of a face recognition system. The End-to-End Cumulative Match Characteristic (E2ECMC) summarizes detection, identity consolidation, and identity retrieval performance. The End-to-End Subject Cumulative …