Development of an Adaptive Trait-Aging Invariant Face Recognition System Using Convolutional Neural Networks

Okokpujie, Kennedy; John, Samuel; Ndujiuba, Charles Uzoanya; Noma‐Osaghae, Etinosa

doi:10.1007/978-981-15-1465-4_41

Cited by 8 publications

(6 citation statements)

References 13 publications

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“…However, the result shows that the FNN model in this work outperforms the one proposed previously by Okokpujie et al [26] and the LSTM model used in this work provided better performance than all other models. Moreover, this work considered eight independent data features compared to the authors in Okokpujie et al [27] who used the eight data features as one feature.…”

Section: Discussionmentioning

confidence: 99%

Congestion Intrusion Detection-Based Method for Controller Area Network Bus: A Case for KIA SOUL Vehicle

Okokpujie¹,

Mughole²,

Badejo³

et al. 2022

MMEP

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In the vehicle industry, connectivity and autonomy are becoming increasingly important features. One of the most used protocols for in-vehicle communication is the Controller Area Network (CAN) bus which manages the communication between networked components. However, the CAN bus, despite its critical importance, lacks sufficient security features to protect its network as well as the overall car system. Thus, vehicle network security is becoming increasingly crucial. Methods of intrusion detection help to improve the security of the in-vehicle network. This work aims to provide a model that enables effective detection of attacks such as fuzzy, DoS, and impersonation using the Deep Feedforward Neural Network (DeepFNN) model as well as the Long Short-Term Memory model. Moreover, the LSTM model presents the most satisfying outcome in terms of precision and recall metrics.

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Section: Discussionmentioning

confidence: 99%

Congestion Intrusion Detection-Based Method for Controller Area Network Bus: A Case for KIA SOUL Vehicle

Okokpujie¹,

Mughole²,

Badejo³

et al. 2022

MMEP

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“…Data augmentation is the process of adding noise to photos in order to boost the quantities [24]. The idea of data augmentation has a long history in literature and everyday life [25][26][27][28][29][30][31]. As a result, we were able to collect a pre-processed FG-NET dataset that included 5010 total face photos and an average of 60 face images per person.…”

Section: Fg-net Dataset Pre-processingmentioning

confidence: 99%

Designing an Adaptive Age-Invariant Face Recognition System for Enhanced Security in Smart Urban Environments

Okokpujie,

Subair

et al. 2023

ISI

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The advent of smart technology in urban environments has often been hailed as the solution to a plethora of contemporary urban challenges, ranging from environmental conservation to waste management and transportation. However, the critical aspect of security, encompassing crime detection and prevention, is frequently overlooked. Moreover, there is a dearth of research exploring the potential disruption of conventional face detection and recognition systems by new smart city surveillance security cameras, particularly those which autonomously update their databases. This paper addresses this gap by proposing the enhancement of security in smart cities through the development of an adaptive Age-Invariant Face Recognition (AIFR) model. A non-intrusive AIFR model was constructed using a convolutional neural network and transfer learning techniques, and was then integrated into surveillance cameras. These cameras, designed to capture the faces of city residents at regular intervals, consequently updated their databases autonomously. Upon testing, the developed model demonstrated its potential to substantially improve security by effectively detecting and identifying the residents and visitors of smart cities, and updating their database profiles. Remarkably, the model retained its effectiveness even with significant age intra-class variation, with the capability to alert relevant authorities about potential criminals or missing individuals. This research underscores the potential of adaptive face recognition systems in bolstering security measures within smart urban environments.

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“…The software component consists of: [19,20]. When the user leaves his or her premises, the application may be armed.…”

Section: Software Descriptionmentioning

confidence: 99%

Development of an Affordable Real-Time IoT-Based Surveillance System Using ESP32 and TWILIO API

Okokpujie,

Young

et al. 2023

IJSSE

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In a global context increasingly concerned with security challenges, the significance of robust surveillance systems cannot be overstated, especially in regions afflicted by vandalism and crime. Despite the growing adoption of video surveillance technologies, their high cost remains a barrier, particularly in lower-income areas, notably in African cities where surveillance implementation is reportedly minimal. This study introduces a cost-effective, real-time surveillance system, integrating the ESP32 microcontroller with an OV2640 (OV) camera and a Pyroelectric Infrared (PIR) sensor, leveraging Internet of Things (IoT) technology. The system is designed to detect motion, alert users via SMS in the event of an intrusion, and transmit real-time video using the TWILIO Application Programming Interface (API), which facilitates global communication through SMS, voice, and wireless services. Upon deployment and testing, it was observed that the system effectively corresponds the visual images on the Ismart platform with the actual real-time video captured within the coverage area. The motion sensor unit demonstrated reliable functionality. A notable outcome of this implementation is the operational cost, which is assessed to be less than 50% of existing surveillance systems, thereby offering a more affordable alternative without compromising efficiency. The proposed system's efficacy and cost-effectiveness position it as a viable solution for a wide range of applications, including domestic settings, banking institutions, office premises, and airports.

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Development of an Adaptive Trait-Aging Invariant Face Recognition System Using Convolutional Neural Networks

Cited by 8 publications

References 13 publications

Congestion Intrusion Detection-Based Method for Controller Area Network Bus: A Case for KIA SOUL Vehicle

Congestion Intrusion Detection-Based Method for Controller Area Network Bus: A Case for KIA SOUL Vehicle

Designing an Adaptive Age-Invariant Face Recognition System for Enhanced Security in Smart Urban Environments

Development of an Affordable Real-Time IoT-Based Surveillance System Using ESP32 and TWILIO API

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