Mahesh K. Banavar
Clarkson University
Signal processingAlgorithmEngineeringEmbedded systemArtificial intelligenceCommunication channelEstimatorMobile deviceElectronic engineeringWireless sensor networkSoftwareFusion centerMathematicsComputer sciencePhotovoltaic systemMultimediaAndroid (operating system)Control theoryReal-time computingFadingDigital signal processing
110Publications
17H-index
790Citations
Publications 105
Newest
#1Mahesh K. BanavarH-Index: 17
Last. Jie SunH-Index: 87
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A main challenge in target localization arises from the lack of reliable distance measures. This issue is especially pronounced in indoor settings due to the presence of walls, floors, furniture, and other dynamically changing conditions such as the movement of people and goods, varying temperature, and airflows. Here, we develop a new computational framework to estimate the location of a target without the need for reliable distance measures. The method, which we term Ordinal UNLOC, uses only o...
#1Kevin MackH-Index: 1
#2Prashant AthavaleH-Index: 7
Last. Erik M. BolltH-Index: 34
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#1Keivan Bahmani (Clarkson University)H-Index: 3
#2Richard Plesh (Clarkson University)H-Index: 1
Last. Stephanie Schuckers (Clarkson University)H-Index: 36
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Face recognition (FR) systems are fast becoming ubiquitous. However, differential performance among certain demographics was identified in several widely used FR models. The skin tone of the subject is an important factor in addressing the differential performance. Previous work has used modeling methods to propose skin tone measures of subjects across different illuminations or utilized subjective labels of skin color and demographic information. However, such models heavily rely on consistent ...
#1Simon Khan (Clarkson University)
#2Cooper Fraser (Clarkson University)
Last. Stephanie Schuckers (Clarkson University)H-Index: 36
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Facebook has become an important part of our daily life. From knowing the status of our relatives, showing off a new car, to connecting with a high school classmate, abundant personally identifiable information (PII) are made visible to others by posts, images and news. However, this free flow of information has also created significant cyber-security challenges that make us vulnerable to social engineering and cyber crimes. To confront these challenges, we propose a new behavioral biometric tha...
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#1Blaine Ayotte (Clarkson University)H-Index: 3
#2Mahesh K. Banavar (Clarkson University)H-Index: 17
Last. Stephanie Schuckers (Clarkson University)H-Index: 36
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Source
A main challenge in target localization arises from the lack of reliable distance measures. This issue is especially pronounced in indoor settings due to the presence of walls, floors, furniture, and other dynamically changing conditions such as the movement of people and goods, varying temperature, and airflows. Here, we develop a new computational framework to estimate the location of a target without the need for reliable distance measures. The method, which we term Ordinal UNLOC, uses only o...
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In this paper, we propose a novel distance-based localization algorithm for multi-user classification in keystroke biometrics. While this method can be applied across identification scenarios, here, we address a use-case to mitigate problems such as Facebook access misuse in shared settings. Our approach combines distance-based metric evaluation, dimensionality reduction, and localization, and is effective in dealing with challenges associated with keystroke dynamics, such as feature interaction...
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#1Blaine AyotteH-Index: 3
#2Mahesh K. BanavarH-Index: 17
Last. Stephanie SchuckersH-Index: 36
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Keystroke dynamics study the way in which users input text via their keyboards. Having the ability to differentiate users, typing behaviors can unobtrusively form a component of a behavioral biometric recognition system to improve existing account security. Keystroke dynamics systems on free-text data have previously required 500 or more characters to achieve reasonable performance. In this paper, we propose a novel instance-based graph comparison algorithm called the instance-based tail area de...
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Keystroke dynamics study the way in which users input text via their keyboards. Having the ability to differentiate users, typing behaviors can unobtrusively form a component of a behavioral biometric recognition system to improve existing account security. Keystroke dynamics systems on free-text data have previously required 500 or more characters to achieve reasonable performance. In this paper, we propose a novel instance-based graph comparison algorithm called the instance-based tail area de...
#1Chinmay Sahu (Clarkson University)
#2Mahesh K. Banavar (Clarkson University)H-Index: 17
Last. M Vanitha (VIT University)
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In this paper, two algorithms are presented that analyze and identify the source of a rotating bar, called a rotor, moving at an unknown speed. Using sensors at known locations on the surface of the rotor, the sensors record the times when the rotor wave/bar passes them. With these data, the first algorithm uses concepts from rotational dynamics and node localization, while the second algorithm relies on the geometry of the sensor placement, to estimate the centre of the rotor. Both algorithms a...
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