Kalp, D.
* 1989: Measuring the Effectiveness of Task-Level Parallelism for High-Level Vision
* 1990: Effectiveness of Task-Level Parallelism for High-Level Vision, The
* 1991: Effectiveness of Task-Level Parallelism for High-Level Vision, The
* 1997: Preliminary Results on the Analysis of HYDICE Data for Information Fusion in Cartographic Feature Extraction
* 1997: Preliminary Results on the Analysis of HYDICE Data for Information Fusion in Cartographic Feature Extraction
* 1997: Research in the Automated Analysis of Remotely Sensed Imagery: 1995-1996
Includes: Kalp, D. Kalp, D.[Dirk]
Kalpakchieva, K.
* 2005: corpus for comparative evaluation of OCR software and postcorrection techniques, A
Kalpakis, G.[George]
* 2019: Identifying Terrorism-Related Key Actors in Multidimensional Social Networks
* 2020: Extensible Framework for Interactive Real-time Visualizations of Large-scale Heterogeneous Multimedia Information from Online Sources, An
Kalpakis, K.
* 2014: Detecting Road Traffic Events by Coupling Multiple Timeseries With a Nonparametric Bayesian Method
Kalpakli, M.[Mehmet]
* 2010: Redif Extraction in Handwritten Ottoman Literary Texts
Kalpana, M.
* 2023: Blackgram Plant Leaves Disease Detection
Kalpana, N.
* 2015: Fast Computation of Generalized Waterfilling Problems
Kalpathi, R.[Ramakrishnan]
* 2015: Respiratory motion prediction from CBCT image observations using UKF
Kalpathi, R.R.[R. Ramakrishnan]
* 2014: Exploring Transfer Learning Approaches for Head Pose Classification from Multi-view Surveillance Images
Kalpathy Cramer, J.[Jayashree]
* 2008: Effectiveness of global features for automatic medical image classification and retrieval: The experiences of OHSU at ImageCLEFmed
* 2010: ImageCLEF Medical Retrieval Task at ICPR 2010: Information Fusion to Combine Visual and Textual Information, The
* 2010: ImageCLEF Medical Retrieval Task at ICPR 2010: Information Fusion, The
* 2013: Contour-based shape representation using principal curves
* 2014: Structure-based level set method for automatic retinal vasculature segmentation
* 2015: Multimodal Brain Tumor Image Segmentation Benchmark (BRATS), The
* 2016: MRI Based Bayesian Personalization of a Tumor Growth Model
* 2017: Personalized Radiotherapy Planning Based on a Computational Tumor Growth Model
* 2021: Lung Nodule Malignancy Prediction in Sequential CT Scans: Summary of ISBI 2018 Challenge
* 2023: FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image Reconstruction
Includes: Kalpathy Cramer, J.[Jayashree] Kalpathy-Cramer, J.[Jayashree] Kalpathy-Cramer, J.
10 for Kalpathy Cramer, J.
Kalpoma, K.A.
* 2007: Image Fusion Processing for IKONOS 1-m Color Imagery