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You searched for +publisher:"Rutgers University" +contributor:("Michmizos, Konstantinos"). Showing records 1 – 15 of 15 total matches.

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Rutgers University

1. Balachandar, Praveenram, 1991-. A neuro-inspired oculomotor controller for a robotic head prototype.

Degree: MS, Computer Science, 2017, Rutgers University

 Robotic vision introduces requirements for real-time processing of fast-varying, noisy information in a continuously changing environment. In a real-world environment, convenient assumptions, such as static… (more)

Subjects/Keywords: Robotics; Neurosciences

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APA (6th Edition):

Balachandar, Praveenram, 1. (2017). A neuro-inspired oculomotor controller for a robotic head prototype. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/53082/

Chicago Manual of Style (16th Edition):

Balachandar, Praveenram, 1991-. “A neuro-inspired oculomotor controller for a robotic head prototype.” 2017. Masters Thesis, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/53082/.

MLA Handbook (7th Edition):

Balachandar, Praveenram, 1991-. “A neuro-inspired oculomotor controller for a robotic head prototype.” 2017. Web. 30 Nov 2020.

Vancouver:

Balachandar, Praveenram 1. A neuro-inspired oculomotor controller for a robotic head prototype. [Internet] [Masters thesis]. Rutgers University; 2017. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/53082/.

Council of Science Editors:

Balachandar, Praveenram 1. A neuro-inspired oculomotor controller for a robotic head prototype. [Masters Thesis]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/53082/


Rutgers University

2. Kumar, Neelesh, 1993-. Vision based cognitive fatigue detection.

Degree: MS, Computer Science, 2017, Rutgers University

 Analyzing human activity is a basic component of any system, be it biological or artificial, that aims to predict future behavior. Tracking and recognizing voluntary… (more)

Subjects/Keywords: Computer vision

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APA (6th Edition):

Kumar, Neelesh, 1. (2017). Vision based cognitive fatigue detection. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/53648/

Chicago Manual of Style (16th Edition):

Kumar, Neelesh, 1993-. “Vision based cognitive fatigue detection.” 2017. Masters Thesis, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/53648/.

MLA Handbook (7th Edition):

Kumar, Neelesh, 1993-. “Vision based cognitive fatigue detection.” 2017. Web. 30 Nov 2020.

Vancouver:

Kumar, Neelesh 1. Vision based cognitive fatigue detection. [Internet] [Masters thesis]. Rutgers University; 2017. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/53648/.

Council of Science Editors:

Kumar, Neelesh 1. Vision based cognitive fatigue detection. [Masters Thesis]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/53648/


Rutgers University

3. Tang, Guangzhi. Gridbot: towards a neuroinspired navigation system for robot planning.

Degree: MS, Computer Science, 2017, Rutgers University

 The ability to orient in an unknown, fast-changing, environment is an unmet challenge for robots but a seamlessly solved problem for the primate brain. This… (more)

Subjects/Keywords: Intelligent control systems; Robots; Space perception

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APA (6th Edition):

Tang, G. (2017). Gridbot: towards a neuroinspired navigation system for robot planning. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/54029/

Chicago Manual of Style (16th Edition):

Tang, Guangzhi. “Gridbot: towards a neuroinspired navigation system for robot planning.” 2017. Masters Thesis, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/54029/.

MLA Handbook (7th Edition):

Tang, Guangzhi. “Gridbot: towards a neuroinspired navigation system for robot planning.” 2017. Web. 30 Nov 2020.

Vancouver:

Tang G. Gridbot: towards a neuroinspired navigation system for robot planning. [Internet] [Masters thesis]. Rutgers University; 2017. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/54029/.

Council of Science Editors:

Tang G. Gridbot: towards a neuroinspired navigation system for robot planning. [Masters Thesis]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/54029/


Rutgers University

4. Khan, Faisal M., 1981-. Semi-supervised transductive regression for survival analysis in medical prognostics.

Degree: PhD, Computer Science, 2016, Rutgers University

The central challenge in predictive modeling for survival analysis in medical prognostics is the management of censored observations in the data. While time-to-event predictions can… (more)

Subjects/Keywords: Survival analysis (Biometry)

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APA (6th Edition):

Khan, Faisal M., 1. (2016). Semi-supervised transductive regression for survival analysis in medical prognostics. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51331/

Chicago Manual of Style (16th Edition):

Khan, Faisal M., 1981-. “Semi-supervised transductive regression for survival analysis in medical prognostics.” 2016. Doctoral Dissertation, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/51331/.

MLA Handbook (7th Edition):

Khan, Faisal M., 1981-. “Semi-supervised transductive regression for survival analysis in medical prognostics.” 2016. Web. 30 Nov 2020.

Vancouver:

Khan, Faisal M. 1. Semi-supervised transductive regression for survival analysis in medical prognostics. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51331/.

Council of Science Editors:

Khan, Faisal M. 1. Semi-supervised transductive regression for survival analysis in medical prognostics. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51331/


Rutgers University

5. Kim, Jongpil, 1977-. Discovering visual saliency for image analysis.

Degree: PhD, Computer Science, 2017, Rutgers University

 Salient object detection is a key step in many image analysis tasks such as object detection and image segmentation, as it not only identifies relevant… (more)

Subjects/Keywords: Computer vision; Image analysis

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APA (6th Edition):

Kim, Jongpil, 1. (2017). Discovering visual saliency for image analysis. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/52218/

Chicago Manual of Style (16th Edition):

Kim, Jongpil, 1977-. “Discovering visual saliency for image analysis.” 2017. Doctoral Dissertation, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/52218/.

MLA Handbook (7th Edition):

Kim, Jongpil, 1977-. “Discovering visual saliency for image analysis.” 2017. Web. 30 Nov 2020.

Vancouver:

Kim, Jongpil 1. Discovering visual saliency for image analysis. [Internet] [Doctoral dissertation]. Rutgers University; 2017. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/52218/.

Council of Science Editors:

Kim, Jongpil 1. Discovering visual saliency for image analysis. [Doctoral Dissertation]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/52218/


Rutgers University

6. Yang, Fan, 1985-. Localization of subthalamic nucleus from microelectrode recordings with k-means clustering.

Degree: MS, Computer Science, 2017, Rutgers University

 Background: Microelectrode recordings (MERs) of the neural activities are a useful tool for subthalamic nucleus localization (STN) in the process of deep brain stimulation (DBS)… (more)

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APA (6th Edition):

Yang, Fan, 1. (2017). Localization of subthalamic nucleus from microelectrode recordings with k-means clustering. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/55776/

Chicago Manual of Style (16th Edition):

Yang, Fan, 1985-. “Localization of subthalamic nucleus from microelectrode recordings with k-means clustering.” 2017. Masters Thesis, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/55776/.

MLA Handbook (7th Edition):

Yang, Fan, 1985-. “Localization of subthalamic nucleus from microelectrode recordings with k-means clustering.” 2017. Web. 30 Nov 2020.

Vancouver:

Yang, Fan 1. Localization of subthalamic nucleus from microelectrode recordings with k-means clustering. [Internet] [Masters thesis]. Rutgers University; 2017. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55776/.

Council of Science Editors:

Yang, Fan 1. Localization of subthalamic nucleus from microelectrode recordings with k-means clustering. [Masters Thesis]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55776/


Rutgers University

7. Yan, Zhennan, 1983-. Robust medical image recognition and segmentation.

Degree: PhD, Computer Science, 2016, Rutgers University

In recent decades, with increasing amount of medical data, clinical trials are designed and conducted to explore whether a medical strategy, treatment, or device is… (more)

Subjects/Keywords: Diagnostic imaging; Computer vision

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APA (6th Edition):

Yan, Zhennan, 1. (2016). Robust medical image recognition and segmentation. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51515/

Chicago Manual of Style (16th Edition):

Yan, Zhennan, 1983-. “Robust medical image recognition and segmentation.” 2016. Doctoral Dissertation, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/51515/.

MLA Handbook (7th Edition):

Yan, Zhennan, 1983-. “Robust medical image recognition and segmentation.” 2016. Web. 30 Nov 2020.

Vancouver:

Yan, Zhennan 1. Robust medical image recognition and segmentation. [Internet] [Doctoral dissertation]. Rutgers University; 2016. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51515/.

Council of Science Editors:

Yan, Zhennan 1. Robust medical image recognition and segmentation. [Doctoral Dissertation]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51515/


Rutgers University

8. Banga, Karansingh, 1991-. Development of an adaptive serious game for assessing cognitive engagement.

Degree: MS, Computer Science, 2019, Rutgers University

 Cognitive Engagement is defined as "The act of beginning and carrying on of activity with a sense of emotional involvement or commitment and the deliberate… (more)

Subjects/Keywords: Nervous system  – Diseases  – Patients  – Rehabilitation  – Technological innovations; Games  – Therapeutic use

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APA (6th Edition):

Banga, Karansingh, 1. (2019). Development of an adaptive serious game for assessing cognitive engagement. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/60588/

Chicago Manual of Style (16th Edition):

Banga, Karansingh, 1991-. “Development of an adaptive serious game for assessing cognitive engagement.” 2019. Masters Thesis, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/60588/.

MLA Handbook (7th Edition):

Banga, Karansingh, 1991-. “Development of an adaptive serious game for assessing cognitive engagement.” 2019. Web. 30 Nov 2020.

Vancouver:

Banga, Karansingh 1. Development of an adaptive serious game for assessing cognitive engagement. [Internet] [Masters thesis]. Rutgers University; 2019. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/60588/.

Council of Science Editors:

Banga, Karansingh 1. Development of an adaptive serious game for assessing cognitive engagement. [Masters Thesis]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/60588/


Rutgers University

9. Shah, Arpit, 1996-. Development of an astrocytic module for spiking neural networks on neuromorphic hardware.

Degree: MS, Spiking neural networks, 2019, Rutgers University

 Astrocytes have long been neglected in application to neuronal networks due to being electrically silent. While these glial cells have been hypothesized to serve as… (more)

Subjects/Keywords: Computer Science; Neural networks (Computer science); Astrocytes

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APA (6th Edition):

Shah, Arpit, 1. (2019). Development of an astrocytic module for spiking neural networks on neuromorphic hardware. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/61054/

Chicago Manual of Style (16th Edition):

Shah, Arpit, 1996-. “Development of an astrocytic module for spiking neural networks on neuromorphic hardware.” 2019. Masters Thesis, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/61054/.

MLA Handbook (7th Edition):

Shah, Arpit, 1996-. “Development of an astrocytic module for spiking neural networks on neuromorphic hardware.” 2019. Web. 30 Nov 2020.

Vancouver:

Shah, Arpit 1. Development of an astrocytic module for spiking neural networks on neuromorphic hardware. [Internet] [Masters thesis]. Rutgers University; 2019. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/61054/.

Council of Science Editors:

Shah, Arpit 1. Development of an astrocytic module for spiking neural networks on neuromorphic hardware. [Masters Thesis]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/61054/


Rutgers University

10. Zhu, Yan, 1986-. Towards active and interactive visual learning.

Degree: PhD, Computer Science, 2017, Rutgers University

Modern computer vision models mostly rely on massive human annotated datasets for supervised training. The models are typically learned from the supervision of static datasets… (more)

Subjects/Keywords: Computer vision

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APA (6th Edition):

Zhu, Yan, 1. (2017). Towards active and interactive visual learning. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/55812/

Chicago Manual of Style (16th Edition):

Zhu, Yan, 1986-. “Towards active and interactive visual learning.” 2017. Doctoral Dissertation, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/55812/.

MLA Handbook (7th Edition):

Zhu, Yan, 1986-. “Towards active and interactive visual learning.” 2017. Web. 30 Nov 2020.

Vancouver:

Zhu, Yan 1. Towards active and interactive visual learning. [Internet] [Doctoral dissertation]. Rutgers University; 2017. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55812/.

Council of Science Editors:

Zhu, Yan 1. Towards active and interactive visual learning. [Doctoral Dissertation]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/55812/


Rutgers University

11. Peng, Xi, 1986-. Learning disentangled representations in deep visual analysis.

Degree: PhD, Computer Science, 2018, Rutgers University

Learning reliable and interpretable representations is one of the fundamental challenges in machine learning and computer vision. Over the last decade, deep neural networks have… (more)

Subjects/Keywords: Machine learning

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APA (6th Edition):

Peng, Xi, 1. (2018). Learning disentangled representations in deep visual analysis. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/56078/

Chicago Manual of Style (16th Edition):

Peng, Xi, 1986-. “Learning disentangled representations in deep visual analysis.” 2018. Doctoral Dissertation, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/56078/.

MLA Handbook (7th Edition):

Peng, Xi, 1986-. “Learning disentangled representations in deep visual analysis.” 2018. Web. 30 Nov 2020.

Vancouver:

Peng, Xi 1. Learning disentangled representations in deep visual analysis. [Internet] [Doctoral dissertation]. Rutgers University; 2018. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/56078/.

Council of Science Editors:

Peng, Xi 1. Learning disentangled representations in deep visual analysis. [Doctoral Dissertation]. Rutgers University; 2018. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/56078/


Rutgers University

12. Yang, Dong, 1987-. Deformable models and machine learning for large-scale cardiac MRI image analytics.

Degree: PhD, Computer Science, 2019, Rutgers University

The analysis of left ventricle (LV) wall motion is an important step for understanding cardiac functioning mechanisms, and clinical diagnosis of ventricular diseases. For example,… (more)

Subjects/Keywords: Heart  – Magnetic resonance imaging; Machine learning

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APA (6th Edition):

Yang, Dong, 1. (2019). Deformable models and machine learning for large-scale cardiac MRI image analytics. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/61044/

Chicago Manual of Style (16th Edition):

Yang, Dong, 1987-. “Deformable models and machine learning for large-scale cardiac MRI image analytics.” 2019. Doctoral Dissertation, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/61044/.

MLA Handbook (7th Edition):

Yang, Dong, 1987-. “Deformable models and machine learning for large-scale cardiac MRI image analytics.” 2019. Web. 30 Nov 2020.

Vancouver:

Yang, Dong 1. Deformable models and machine learning for large-scale cardiac MRI image analytics. [Internet] [Doctoral dissertation]. Rutgers University; 2019. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/61044/.

Council of Science Editors:

Yang, Dong 1. Deformable models and machine learning for large-scale cardiac MRI image analytics. [Doctoral Dissertation]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/61044/


Rutgers University

13. Gindra, Rushin Hitesh, 1996-. Improvements in cardiac segmentation for cross-modality domain adaptation.

Degree: MS, Unsupervised domain adaptation, 2020, Rutgers University

 In medical image computing, the problem of heterogeneous domain shift is quite common and severe, causing many deep convolutional networks to under-perform on various imaging… (more)

Subjects/Keywords: Diagnostic imaging; Computer Science

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APA (6th Edition):

Gindra, Rushin Hitesh, 1. (2020). Improvements in cardiac segmentation for cross-modality domain adaptation. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/64100/

Chicago Manual of Style (16th Edition):

Gindra, Rushin Hitesh, 1996-. “Improvements in cardiac segmentation for cross-modality domain adaptation.” 2020. Masters Thesis, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/64100/.

MLA Handbook (7th Edition):

Gindra, Rushin Hitesh, 1996-. “Improvements in cardiac segmentation for cross-modality domain adaptation.” 2020. Web. 30 Nov 2020.

Vancouver:

Gindra, Rushin Hitesh 1. Improvements in cardiac segmentation for cross-modality domain adaptation. [Internet] [Masters thesis]. Rutgers University; 2020. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/64100/.

Council of Science Editors:

Gindra, Rushin Hitesh 1. Improvements in cardiac segmentation for cross-modality domain adaptation. [Masters Thesis]. Rutgers University; 2020. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/64100/

14. Rennie, Colin M., 1988-. Designing and learning CPG gaits for spherical tensegrity robots using Bayesian optimization.

Degree: MS, Computer Science, 2018, Rutgers University

 This thesis presents a framework for developing a library of gaits for highly non-linear, hyper-redundant, potentially compliant robotic systems. Examples of such systems that motivate… (more)

Subjects/Keywords: Robotics

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APA (6th Edition):

Rennie, Colin M., 1. (2018). Designing and learning CPG gaits for spherical tensegrity robots using Bayesian optimization. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/56083/

Chicago Manual of Style (16th Edition):

Rennie, Colin M., 1988-. “Designing and learning CPG gaits for spherical tensegrity robots using Bayesian optimization.” 2018. Masters Thesis, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/56083/.

MLA Handbook (7th Edition):

Rennie, Colin M., 1988-. “Designing and learning CPG gaits for spherical tensegrity robots using Bayesian optimization.” 2018. Web. 30 Nov 2020.

Vancouver:

Rennie, Colin M. 1. Designing and learning CPG gaits for spherical tensegrity robots using Bayesian optimization. [Internet] [Masters thesis]. Rutgers University; 2018. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/56083/.

Council of Science Editors:

Rennie, Colin M. 1. Designing and learning CPG gaits for spherical tensegrity robots using Bayesian optimization. [Masters Thesis]. Rutgers University; 2018. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/56083/

15. Trivedi, Chintan, 1993-. Camera based detection of the onset of cognitive fatigue.

Degree: MS, Computer Science, 2017, Rutgers University

 The onset of cognitive fatigue is associated with a period of transient, subconscious decrease in maximal cognitive ability, typically influencing decision making. The ability to… (more)

Subjects/Keywords: Machine learning; Mental fatigue

…sent over to Rutgers University for the purpose of this research work. 2.1.2 Experiment… 

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APA (6th Edition):

Trivedi, Chintan, 1. (2017). Camera based detection of the onset of cognitive fatigue. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/54034/

Chicago Manual of Style (16th Edition):

Trivedi, Chintan, 1993-. “Camera based detection of the onset of cognitive fatigue.” 2017. Masters Thesis, Rutgers University. Accessed November 30, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/54034/.

MLA Handbook (7th Edition):

Trivedi, Chintan, 1993-. “Camera based detection of the onset of cognitive fatigue.” 2017. Web. 30 Nov 2020.

Vancouver:

Trivedi, Chintan 1. Camera based detection of the onset of cognitive fatigue. [Internet] [Masters thesis]. Rutgers University; 2017. [cited 2020 Nov 30]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/54034/.

Council of Science Editors:

Trivedi, Chintan 1. Camera based detection of the onset of cognitive fatigue. [Masters Thesis]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/54034/

.