Journal ArticleDOI
Pattern Recognition and Machine Learning
TLDR
This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.Abstract:
(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366.read more
Citations
More filters
Journal ArticleDOI
Medical Image Segmentation Methods, Algorithms, and Applications
Alireza Norouzi,Mohd Shafry Mohd Rahim,Ayman Altameem,Tanzila Saba,Abdolvahab Ehsani Rad,Amjad Rehman,Mueen Uddin +6 more
TL;DR: The latest segmentation methods applied in medical image analysis are described and the advantages and disadvantages of each method are described besides examination of each algorithm with its application in Magnetic Resonance Imaging and Computed Tomography image analysis.
Journal ArticleDOI
Multi-Orientation Scene Text Detection with Adaptive Clustering
TL;DR: A unified distance metric learning framework for adaptive hierarchical clustering, which can simultaneously learn similarity weights and the clustering threshold, and an effective multi-orientation scene text detection system, which constructs text candidates by grouping characters based on this adaptive clustering.
Journal ArticleDOI
k-nearest neighbors in uncertain graphs
TL;DR: Novel distance functions that extend well-known graph concepts, such as shortest paths are proposed that outperform previously used alternatives in identifying true neighbors in real-world biological data and scale for graphs with tens of millions of edges.
Journal ArticleDOI
System Identification and Estimation Framework for Pivotal Automotive Battery Management System Characteristics
TL;DR: A BMS that estimates the critical characteristics of the battery (such as SOC, SOH, and RUL) using a data-driven approach is proposed and the proposed framework provides a systematic way for estimating relevant battery characteristics with a high-degree of accuracy.
Journal ArticleDOI
Probabilistic Models for Inference about Identity
TL;DR: This paper considers each image as having been generated from several underlying causes, some of which are due to identity (latent identity variables, or LIVs), and develops a series of novel generative models which incorporate both within-individual and between-individual variation.