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Articles 2101 - 2130 of 7215
Full-Text Articles in Computer Engineering
A Supervised Learning Approach For Detecting Erroneoussamples In Embeddings, Görkem Saygili
A Supervised Learning Approach For Detecting Erroneoussamples In Embeddings, Görkem Saygili
Turkish Journal of Electrical Engineering and Computer Sciences
Visualizing multidimensional data has been a crucial task in recent years regarding the growing amount of data from various sources. To achieve this, dimensionality reduction algorithms have been used to reduce the number of dimensions for visualization of the data on a screen. However, these algorithms may fail to faithfully represent high dimensional data in lower dimensions and eventually lead to erroneous visualizations. In this work, we propose an error detection algorithm for dimensionality reduction algorithms based on recently developed error prediction algorithms for medical image registration. The proposed algorithm matches the neighborhoods of high and low dimensional data with …
Comparative Study Between Measured And Estimated Wind Energy Yield, Ayman Alquraan, Mohammed Al-Mahmodi, Ashraf Radaideh, Hussein Al-Masri
Comparative Study Between Measured And Estimated Wind Energy Yield, Ayman Alquraan, Mohammed Al-Mahmodi, Ashraf Radaideh, Hussein Al-Masri
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a power-speed (P-V) model of the wind turbine by assuming three different functions for the first performance region; cubic, quadratic and uncorrected cubic. These three functions have been compared with the manufacturer models of five different wind turbines which were installed in five different locations in Jordan; Tafila, Hofa, Fujeij, Al Rajef, and Deahan. The wind turbine of these wind farms are considered as large scale HAWT in the range of Mw. The generated P-V models are developed by applying a new method described in this paper which is basically based on generating a multiplier factor x. …
Distribution Network Reconfiguration Based On Artificial Networkreconfiguration For Variable Load Profile, Hesham Hanie Youssef, Hazlie Bin Mokhlis, Mohamad Sofian Abu Talip, Mohammad Alsamman, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Distribution Network Reconfiguration Based On Artificial Networkreconfiguration For Variable Load Profile, Hesham Hanie Youssef, Hazlie Bin Mokhlis, Mohamad Sofian Abu Talip, Mohammad Alsamman, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Turkish Journal of Electrical Engineering and Computer Sciences
Network reconfiguration is a process to change the open-switches in distribution system for a minimum power loss. In the past, metaheuristic techniques were applied widely for network reconfiguration with consideration of a fixed loading profile. When the loading changes, the current configuration may not be the optimal one. Thus, the technique needs to be executed to find a new optimal configuration based on the latest loading. The process is time-consuming since metaheuristic techniques commonly require high computational times and produces inconsistent results. Therefore, this paper proposes a network reconfiguration technique based on artificial neural network (ANN) for variable loading conditions. …
A Novel Grouping Proof Authentication Protocol For Lightweight Devices:Gpapxr+, Ömer Aydin, Gökhan Dalkiliç, Cem Kösemen
A Novel Grouping Proof Authentication Protocol For Lightweight Devices:Gpapxr+, Ömer Aydin, Gökhan Dalkiliç, Cem Kösemen
Turkish Journal of Electrical Engineering and Computer Sciences
Radio frequency identification (RFID) tags that meet EPC Gen2 standards are used in many fields such as supply chain operations. The number of the RFID tags, smart cards, wireless sensor nodes, and Internet of things devices is increasing day by day and the areas where they are used are expanding. These devices are very limited in terms of the resources they have. For this reason, many security mechanisms developed for existing computer systems cannot be used for these devices. In order to ensure secure communication, it is necessary to provide authentication process between these lightweight devices and the devices they …
Exhaustive Hard Triplet Mining Loss For Person Re-Identification, Chao Xu, Xiang Sun, Ziliang Chen, Shoubiao Tan
Exhaustive Hard Triplet Mining Loss For Person Re-Identification, Chao Xu, Xiang Sun, Ziliang Chen, Shoubiao Tan
Turkish Journal of Electrical Engineering and Computer Sciences
Person reidentification (Re-ID) is an important task in computer vision and has many applications in videobased surveillance. Recently, the triplet loss has been popular in the deep learning framework for person Re-ID. It is particularly important to note that the selection of hard triplets has significant influence on the performance of the learned deep model. However, the existing triplet losses only focus on some specific forms of hard triplets, thus leading to weaker generalization capability. To address this issue, we propose a novel variant of the triplet loss, named exhaustive hard triplet mining loss (EHTM), which is able to deal …
Exploring The Parameter Space Of Human Activity Recognition With Mobile Devices, Berrenur Saylam, Muhammad Shoaib, Özlem Durmaz İncel
Exploring The Parameter Space Of Human Activity Recognition With Mobile Devices, Berrenur Saylam, Muhammad Shoaib, Özlem Durmaz İncel
Turkish Journal of Electrical Engineering and Computer Sciences
Motion sensors available on smart phones make it possible to recognize human activities. Accelerometer, gyroscope, magnetometer, and their various combinations are used to classify, particularly, locomotion activities, ranging from walking to biking. In most of the studies, the focus is on the collection of data and on the analysis of the impact of different parameters on the recognition performance. The parameter space includes the types of sensors used, features, classification algorithms, and position/orientation of the mobile device. In most of the studies, the impact of some of these parameters is partially analyzed; however, in this work, we investigate the parameter …
Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose
Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose
Turkish Journal of Electrical Engineering and Computer Sciences
Internet usage has increased rapidly with the development of information communication technologies. The increase in internet usage led to the growth of data volumes on the internet and the emergence of the big data concept. Therefore, it has become even more important to analyze the data and make it meaningful. In this study, 690 million queries and approximately 5.9 quadrillion data collected daily from different servers were recorded on the Redis servers by using real-time big data analysis method and load balance structure for a company operating in the tourism sector. Here, wireless networks were used as a triggering factor …
Efficient Turkish Tweet Classification System For Crisis Response, Saed Alqaraleh, Merve Işik
Efficient Turkish Tweet Classification System For Crisis Response, Saed Alqaraleh, Merve Işik
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a convolutional neural networks Turkish tweet classification system for crisis response. This system has the ability to classify the present information before or during any crisis. In addition, a preprocessing model was also implemented and integrated as a part of the developed system. This paper presents the first ever Turkish tweet dataset for crisis response, which can be widely used and improve similar studies. This dataset has been carefully preprocessed, annotated, and well organized. It is suitable to be used by all the well-known natural language processing tools. Extensive experimental work, using our produced Turkish tweet dataset …
Adaptive Fast Sliding Neural Control For Robot Manipulator, Bariş Özyer
Adaptive Fast Sliding Neural Control For Robot Manipulator, Bariş Özyer
Turkish Journal of Electrical Engineering and Computer Sciences
Robotic manipulators are open to external disturbances and actuation failures during performing a task such as trajectory tracking. In this paper, we present a modifed controller consisting of a global fast sliding surface combined with an adaptive neural network which is called adaptive fast sliding neural control (AFSNC) for a robotic manipulator to precise stable trajectory tracking performance under the external disturbances. The adaptive term is employedtoreduce uncertainties due to unmodeled dynamics. Trackingerror asymptoticallyconvergesto zero according to the Lyapunov stability theorem. Numerical examples have been carried on a planar two-links manipulator to verify the control approach efficiency. The experimental results …
Design And Application Of Spwm Based 21-Level Hybrid Inverter For Induction Motor Drive, Sheikh Tanzim Meraj, Kamrul Hasan, Ammar Masaoud
Design And Application Of Spwm Based 21-Level Hybrid Inverter For Induction Motor Drive, Sheikh Tanzim Meraj, Kamrul Hasan, Ammar Masaoud
Turkish Journal of Electrical Engineering and Computer Sciences
Thispaperpresentstheapplicationofanewlydeveloped21-levelhybridmultilevelinverter. Ahighfrequency modulation technique known as sinusoidal pulse width modulation (SPWM) is applied to the hybrid inverter. This modulation methodology operates the switching sequences of the multilevel inverter to produce the desired 21-level output voltage. To validate the proper application of this inverter, it is further utilized to maintain the speed of a single phase induction motor. The velocity control of the motor is established on the principle of V/f control technique. The speed control strategy along with the compatibility of the SPWM modulation technique were verified by means of simulation and experimental results.
Influence Of Varying Magnet Pole-Arcs And Step-Skew On Permanent Magnet Ac Synchronous Motor Performance, Meti̇n Aydin, Oğuzhan Ocak, Yücel Demi̇r
Influence Of Varying Magnet Pole-Arcs And Step-Skew On Permanent Magnet Ac Synchronous Motor Performance, Meti̇n Aydin, Oğuzhan Ocak, Yücel Demi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Minimization or elimination of cogging torque is a significant issue in permanent magnet (PM) motor design process. There are some design techniques to reduce or eliminate this unwanted torque components in PM motors. This paper focuses on two different design techniques, varying magnet pole-arc and step-skew, to reduce cogging torque component in radial flux PM synchronous motors. Different design points which consider pulsating torque components and back-EMF harmonics are obtained via finite element analysis (FEA) for a low power industrial PM motor. A prototype motor is manufactured for one of the desired designs and is tested experimentally. Good agreement is …
Gated Recurrent Unit Based Demand Response For Preventing Voltage Collapse In A Distribution System, Venkateswarlu Gundu, Sishaj Pulikottil Simon, Kinattingal Sundareswaran, Srinivasa Rao Nayak Panugothu
Gated Recurrent Unit Based Demand Response For Preventing Voltage Collapse In A Distribution System, Venkateswarlu Gundu, Sishaj Pulikottil Simon, Kinattingal Sundareswaran, Srinivasa Rao Nayak Panugothu
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents the application of deep learning algorithms towards demand response management. Demand limit violation and voltage stability are the major problems associated with a secondary distribution system. These problems are solved using demand response models by day ahead scheduling loads at every 15 min interval through linear integer programming and based on short term forecasting of load (kW). A new architecture for short term load forecasting is presented namely gated recurrent unit in which statistical analysis is carried out to get the optimal architecture of the neural network model. Reliability indices such as loss of load probability (LOLP) …
A New Smart Networking Architecture For Container Network Functions, Gülsüm Atici, Pinar Bölük
A New Smart Networking Architecture For Container Network Functions, Gülsüm Atici, Pinar Bölük
Turkish Journal of Electrical Engineering and Computer Sciences
5G slices have challenging application demands from a wide variety of fields including high bandwidth, low latency and reliability. The requirements of the container network functions which are used in telecommunications are different from any other cloud native IT applications as they are used for data plane packet processing functions, together with control, signalling and media processing which have critical processing requirements. This study aims to discover high performing container networking solution by considering traffic loads and application types. The behaviour of several container cluster networking solutions -- Flannel, Weave, Libnetwork, Open Virtual Networking for Open vSwitch and Calico -- …
Adaptive Object Detection For Autonomous Vehicles, Christopher Wolfe
Adaptive Object Detection For Autonomous Vehicles, Christopher Wolfe
Graduate Research Theses & Dissertations
Autonomous vehicles are gradually entering our daily lives. The goal of fully autonomous commercially available vehicles is becoming closer to reality each day as the contributions from researchers and various institutions are being added to the overall body of knowledge. Object detection is a critical component of an autonomous or semi-autonomous vehicle and draws extensively on results from many fields such as image processing and statistics. In this thesis, we consider ideas from the study of real-time computing and control systems to present a novel method of real-time adaptive object detection. We present a conceptual framework of the method as …
A Multi-Constraint Predictive Control System With Auxiliary Emergency Controllerfor Autonomous Vehicles, Farhad Partovi Ebrahimpour
A Multi-Constraint Predictive Control System With Auxiliary Emergency Controllerfor Autonomous Vehicles, Farhad Partovi Ebrahimpour
Graduate Research Theses & Dissertations
In the last few years, several research groups and companies have worked on developing autonomous vehicles. Among the first automation layers, the safety layer plays a significant role in this field. However, considering safety should not diminish the importance of the efficiency of the vehicle in terms of path tracking with the desired speed. This thesis introduces a multi-constraint predictive control algorithm along with a safety layer to guarantee object avoidance in emergency situations. First, there is a quick review of autonomous cars and their functionalities. In the following, a controller switching mechanism is proposed and designed. It switches the …
Real-Time Urban Weather Observations For Urban Air Mobility, Kevin A. Adkins, Mustafa Akbas, Marc Compere
Real-Time Urban Weather Observations For Urban Air Mobility, Kevin A. Adkins, Mustafa Akbas, Marc Compere
International Journal of Aviation, Aeronautics, and Aerospace
Cities of the future will have to overcome congestion, air pollution and increasing infrastructure cost while moving more people and goods smoothly, efficiently and in an eco-friendly manner. Urban air mobility (UAM) is expected to be an integral component of achieving this new type of city. This is a new environment for sustained aviation operations. The heterogeneity of the urban fabric and the roughness elements within it create a unique environment where flight conditions can change frequently across very short distances. UAM vehicles with their lower mass, more limited thrust and slower speeds are especially sensitive to these conditions. Since …
Techno-Economic Analysis Of Diethyl Ether Production Via Catalytic Dehydration Of Ethanol, Boonraksa Chaiapha
Techno-Economic Analysis Of Diethyl Ether Production Via Catalytic Dehydration Of Ethanol, Boonraksa Chaiapha
Chulalongkorn University Theses and Dissertations (Chula ETD)
The major source of energy comes from non-renewable fuels, which have a non-sustainability and negative impact on the environment. Thus, there is change to renewable fuels as bioethanol. Diethyl ether (DEE) is a part of bioethanol. However, the increase of electric vehicles (EV) may decrease ethanol demand for biofuel in the future. Thus, it will be interesting in adding value to ethanol via the catalytic dehydration to produce DEE by conduct techno-economic analysis. Further, there is comparison on different concentrations of ethanol (93% and 95% ethanol) that affect DEE production. For simulation part, the DEE capacity of 3,600 tons/year is …
Implementation Of Traffic Engineering With Segment Routing And Opendaylight Controller On Emulated Virtual Environment Next Generation (Eve-Ng), Htain Lynn Aung
Implementation Of Traffic Engineering With Segment Routing And Opendaylight Controller On Emulated Virtual Environment Next Generation (Eve-Ng), Htain Lynn Aung
Chulalongkorn University Theses and Dissertations (Chula ETD)
Internet service providers and enterprise networks face rapid changes and rapid growth of the internet, and the networks become complex in operations to support the strict Service-level Agreements (SLAs) needed applications. Segment Routing (SR) is a source routing technology that overcomes the conventional Multiprotocol Label Switching (MPLS) networks' drawbacks in scalability, flexibility, and applicability in Software-defined Networking (SDN). SR enables the source device to instruct the path using a segment or list of segments to go through the network. SR can be implemented in IPv6 and MPLS. A segment can be defined as information that instructs SR capable nodes to …
A Morphable Fpga Soft Processor Using Llvm Infrastructure Targeting Low-Power Application-Specific Embedded Systems, Ehsan Ali
Chulalongkorn University Theses and Dissertations (Chula ETD)
The reconfigurable computing (RC) aims to combine the flexibility of General-Purpose Processor (GPP) with performance of Application Specific Integrated Circuits (ASIC). There are several architectures proposed since RC's inception in 1960s, but all have failed to become mainstream. The main factor preventing RC to become common practice is its requirement for implementers of algorithms (programmers) to be familiar with hardware design. In RC, a hardened processor cooperates with a dynamic reconfigurable Hardware Accelerator (HA) which is implemented on Field-Programmable Gate Array (FPGA). The HA implements crucial software kernel on hardware to increase performance and its design demands digital circuit expertise. …
Systematic Model-Based Design Assurance And Property-Based Fault Injection For Safety Critical Digital Systems, Athira Varma Jayakumar
Systematic Model-Based Design Assurance And Property-Based Fault Injection For Safety Critical Digital Systems, Athira Varma Jayakumar
Theses and Dissertations
With advances in sensing, wireless communications, computing, control, and automation technologies, we are witnessing the rapid uptake of Cyber-Physical Systems across many applications including connected vehicles, healthcare, energy, manufacturing, smart homes etc. Many of these applications are safety-critical in nature and they depend on the correct and safe execution of software and hardware that are intrinsically subject to faults. These faults can be design faults (Software Faults, Specification faults, etc.) or physically occurring faults (hardware failures, Single-event-upsets, etc.). Both types of faults must be addressed during the design and development of these critical systems. Several safety-critical industries have widely adopted …
Applications Of Artificial Intelligence To Cryptography, Jonathan Blackledge, Napo Mosola
Applications Of Artificial Intelligence To Cryptography, Jonathan Blackledge, Napo Mosola
Articles
This paper considers some recent advances in the field of Cryptography using Artificial Intelligence (AI). It specifically considers the applications of Machine Learning (ML) and Evolutionary Computing (EC) to analyze and encrypt data. A short overview is given on Artificial Neural Networks (ANNs) and the principles of Deep Learning using Deep ANNs. In this context, the paper considers: (i) the implementation of EC and ANNs for generating unique and unclonable ciphers; (ii) ML strategies for detecting the genuine randomness (or otherwise) of finite binary strings for applications in Cryptanalysis. The aim of the paper is to provide an overview on …
Route Planning For Long-Term Robotics Missions, Christopher Alexander Arend Tatsch
Route Planning For Long-Term Robotics Missions, Christopher Alexander Arend Tatsch
Graduate Theses, Dissertations, and Problem Reports (ETD)
Many future robotic applications such as the operation in large uncertain environment depend on a more autonomous robot. The robotics long term autonomy presents challenges on how to plan and schedule goal locations across multiple days of mission duration. This is an NP-hard problem that is infeasible to solve for an optimal solution due to the large number of vertices to visit. In some cases the robot hardware constraints also adds the requirement to return to a charging station multiple times in a long term mission. The uncertainties in the robot model and environment require the robot planner to account …
Alone: A Dataset For Toxic Behavior Among Adolescents On Twitter, Thilini Wijesiriwardene, Hale Inan, Ugur Kursuncu, Manas Gaur, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth, I. Budak Arpinar
Alone: A Dataset For Toxic Behavior Among Adolescents On Twitter, Thilini Wijesiriwardene, Hale Inan, Ugur Kursuncu, Manas Gaur, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth, I. Budak Arpinar
Publications
The convenience of social media has also enabled its misuse, potentially resulting in toxic behavior. Nearly 66% of internet users have observed online harassment, and 41% claim personal experience, with 18% facing severe forms of online harassment. This toxic communication has a significant impact on the well-being of young individuals, affecting mental health and, in some cases, resulting in suicide. These communications exhibit complex linguistic and contextual characteristics, making recognition of such narratives challenging. In this paper, we provide a multimodal dataset of toxic social media interactions between confirmed high school students, called ALONE (AdoLescents ON twittEr), along with descriptive …
Palmprint Gender Classification Using Deep Learning Methods, Minou Khayami
Palmprint Gender Classification Using Deep Learning Methods, Minou Khayami
Graduate Theses, Dissertations, and Problem Reports (ETD)
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 …
A Sample Weight And Adaboost Cnn-Based Coarse To Fine Classification Of Fruit And Vegetables At A Supermarket Self-Checkout, Khurram Hameed, Douglas Chai, Alexander Rassau
A Sample Weight And Adaboost Cnn-Based Coarse To Fine Classification Of Fruit And Vegetables At A Supermarket Self-Checkout, Khurram Hameed, Douglas Chai, Alexander Rassau
Research outputs 2014 to 2021
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The physical features of fruit and vegetables make the task of vision-based classification of fruit and vegetables challenging. The classification of fruit and vegetables at a supermarket self-checkout poses even more challenges due to variable lighting conditions and human factors arising from customer interactions with the system along with the challenges associated with the colour, texture, shape, and size of a fruit or vegetable. Considering this complex application, we have proposed a progressive coarse to fine classification technique to classify fruit and vegetables at supermarket checkouts. The image and weight of …
Fiber-Optic Temperature And Flow Sensory System And Methods, Ming Han, Guigen Liu, Weilin Hou, Qiwen Shen
Fiber-Optic Temperature And Flow Sensory System And Methods, Ming Han, Guigen Liu, Weilin Hou, Qiwen Shen
Department of Electrical and Computer Engineering: Faculty Publications
A fiber optic sensor, a process for utilizing a fiber optic sensor, and a process for fabricating a fiber optic sensor are described, where a double-side-polished silicon pillar is attacked to an optical fiber tip and forms, a Fabry-Perot cavity. In an implementation, a fiber optic sensor in accordance with an examplary embodiment includes an optical fiber configured to be coupled to a light source and a spectrometer; and a single silicon layer or multiple silicon layers disposed on an end face of the optical fiber, where each of the silicon layer(s) defines a Fabry-Perot interferometer, and where the sensor …
Generating Energy Data For Machine Learning With Recurrent Generative Adversarial Networks, Mohammad Navid Fekri, Ananda M. Ghosh, Katarina Grolinger
Generating Energy Data For Machine Learning With Recurrent Generative Adversarial Networks, Mohammad Navid Fekri, Ananda M. Ghosh, Katarina Grolinger
Electrical and Computer Engineering Publications
The smart grid employs computing and communication technologies to embed intelligence into the power grid and, consequently, make the grid more efficient. Machine learning (ML) has been applied for tasks that are important for smart grid operation including energy consumption and generation forecasting, anomaly detection, and state estimation. These ML solutions commonly require sufficient historical data; however, this data is often not readily available because of reasons such as data collection costs and concerns regarding security and privacy. This paper introduces a recurrent generative adversarial network (R-GAN) for generating realistic energy consumption data by learning from real data. Generativea adversarial …
On Algebraic Structures And Automaton For Optimal Computer Network Design And Performance Study, Xiangrong Ma
On Algebraic Structures And Automaton For Optimal Computer Network Design And Performance Study, Xiangrong Ma
UNLV Theses, Dissertations, Professional Papers, and Capstones
For decades, study of computer networks has been concentrated on the use of the well-established OSI or TCP/IP reference models that have found tremendous success in the actual implementation of various network structures and protocols. Lack of theoretical foundation, this implementation-driven, empirical approach, however, is experiencing insurmountable difficulties in delivering, tuning for, and sustaining the promised peak performance of a computer system that is so heavily dependent on the performance of the underline computer networks. This issue is becoming particularly prevalent in today’s cloud-based high-performance computing environment where CPU-time-extensive computation loads need to get distributed among computing machines through high-speed …
Localized Dielectric Loss Heating In Dielectrophoresis Devices, Tae Joon Kwak, Imtiaz Hossen, Rashid Bashir, Woo-Jin Chang, Chung-Hoon Lee
Localized Dielectric Loss Heating In Dielectrophoresis Devices, Tae Joon Kwak, Imtiaz Hossen, Rashid Bashir, Woo-Jin Chang, Chung-Hoon Lee
Electrical and Computer Engineering Faculty Research and Publications
Temperature increases during dielectrophoresis (DEP) can affect the response of biological entities, and ignoring the effect can result in misleading analysis. The heating mechanism of a DEP device is typically considered to be the result of Joule heating and is overlooked without an appropriate analysis. Our experiment and analysis indicate that the heating mechanism is due to the dielectric loss (Debye relaxation). A temperature increase between interdigitated electrodes (IDEs) has been measured with an integrated micro temperature sensor between IDEs to be as high as 70 °C at 1.5 MHz with a 30 Vpp applied voltage to our ultra-low …
Founding The Domain Of Ai Forensics, Ibrahim Baggili, Vahid Behzadan
Founding The Domain Of Ai Forensics, Ibrahim Baggili, Vahid Behzadan
Electrical & Computer Engineering and Computer Science Faculty Publications
With the widespread integration of AI in everyday and critical technologies, it seems inevitable to witness increasing instances of failure in AI systems. In such cases, there arises a need for technical investigations that produce legally acceptable and scientifically indisputable findings and conclusions on the causes of such failures. Inspired by the domain of cyber forensics, this paper introduces the need for the establishment of AI Forensics as a new discipline under AI safety. Furthermore, we propose a taxonomy of the subfields under this discipline, and present a discussion on the foundational challenges that lay ahead of this new research …