Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- <p>Cervix uteri -- Cancer<br />Cancer -- Histopathology<br />Image processing</p> (1)
- <p>Printed circuits -- Design<br />Dielectric devices<br />Signal integrity (Electronics) -- Microwave measurements -- Computer simulation<br />Optical fiber communication</p> (1)
- Cervical cancer (1)
- Classification (1)
- Clustering (1)
- Publication
- Publication Type
Articles 1 - 6 of 6
Full-Text Articles in Physical Sciences and Mathematics
Vehicle Base Station, Emad William Saad, John L. Vian, Matthew A. Vavrina, Jared A. Nisbett, Donald C. Wunsch
Vehicle Base Station, Emad William Saad, John L. Vian, Matthew A. Vavrina, Jared A. Nisbett, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
A system to load and unload material from a vehicle comprises a vehicle base station and an assembly to autonomously load and unload material from the vehicle.
Automated Classification Of Malignant Melanoma Based On Detection Of Atypical Pigment Network In Dermoscopy Images Of Skin Lesions, Nabin K. Mishra
Automated Classification Of Malignant Melanoma Based On Detection Of Atypical Pigment Network In Dermoscopy Images Of Skin Lesions, Nabin K. Mishra
Doctoral Dissertations
“Melanoma causes more deaths than any other form of skin cancer. Early melanoma detection is important to prevent progression to a more deadly stage. Automated computer-based identification of melanoma from dermoscopic images of skin lesions is the most efficient method in early diagnosis. An automated melanoma identification system must include multiple steps, involving lesion segmentation, feature extraction, feature combination and classification. In this research, a classifier-based approach for automatically selecting a lesion border mask for segmentation of dermoscopic skin lesion images is presented. A logistic regression based model selects a single lesion border mask from multiple border masks generated by …
Hidden Markov Model With Information Criteria Clustering And Extreme Learning Machine Regression For Wind Forecasting, Dao Lam, Shuhui Li, Donald C. Wunsch
Hidden Markov Model With Information Criteria Clustering And Extreme Learning Machine Regression For Wind Forecasting, Dao Lam, Shuhui Li, Donald C. Wunsch
Electrical and Computer Engineering Faculty Research & Creative Works
This paper proposes a procedural pipeline for wind forecasting based on clustering and regression. First, the data are clustered into groups sharing similar dynamic properties. Then, data in the same cluster are used to train the neural network that predicts wind speed. For clustering, a hidden Markov model (HMM) and the modified Bayesian information criteria (BIC) are incorporated in a new method of clustering time series data. to forecast wind, a new method for wind time series data forecasting is developed based on the extreme learning machine (ELM). the clustering results improve the accuracy of the proposed method of wind …
Microwave Assisted Reconstruction Of Optical Interferograms For Distributed Fiber Optics Sensing & Characterization Of Pcb Dielectric Properties Using Two Striplines On The Same Board, Lei Hua
Masters Theses
"A new concept, the microwave-assisted reconstruction of an optical interferogram for distributed sensing, was developed to resolve both the position and reflectivity of each sensor along an optical fiber. This approach involves sending a microwave-modulated optical signal through cascaded fiber optic interferometers. The optical spectrum of each sensor can be reconstructed by sweeping the optical wavelength and detecting the modulation signal. A series of cascaded fiber optic extrinsic Fabry-Perot interferometric sensors was used to prove the concept. The microwave-reconstructed interferogram matched well with those recorded individually from a traditional optical spectrometer. The application of distributed strain measurement was also investigated. …
Cervical Cancer Histology Image Feature Extraction And Classification, Peng Guo
Cervical Cancer Histology Image Feature Extraction And Classification, Peng Guo
Masters Theses
"Cervical cancer, the second most common cancer affecting women worldwide and the most common in developing countries can be cured if detected early and treated. Expert pathologists routinely visually examine histology slides for cervix tissue abnormality assessment. In previous research, an automated, localized, fusion-based approach was investigated for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on image analysis of 62 digitized histology images obtained through the National Library of Medicine. In this research, CIN grade assessments from two pathologists are analyzed and are used to facilitate atypical cell concentration feature development …
Adaptive Resonance Theory And Diffusion Maps For Clustering Applications In Pattern Analysis, Donald C. Wunsch, David J. Morris, Rui Xu
Adaptive Resonance Theory And Diffusion Maps For Clustering Applications In Pattern Analysis, Donald C. Wunsch, David J. Morris, Rui Xu
Electrical and Computer Engineering Faculty Research & Creative Works
Adaptive Resonance is primarily a theory that learning is regulated by resonance phenomena in neural circuits. Diffusion maps are a class of kernel methods on edge-weighted graphs. While either of these approaches have demonstrated success in image analysis, their combination is particularly effective. These techniques are reviewed and some example applications are given.