I’ve got the February issue of the IEEE Transactions on Pattern Analysis and Machine Intelligence lying on my coffee table. Let’s evesdrop on what the professionals are up to
Offline loop investigation for handwriting analysis
Robust Face Recognition via Sparse Representation
Natural Image Statistics and Low-Complexity Feature Selection
An analysis of Ensemble Pruning Techniques Based on Ordered Aggregation
Geometric Mean for Subspace Selection
Semisupervised Learning of Hidden Markov Models via a Homotopy Method
Outlier Detection with the Kernelized Spatial Depth Function
Time Warp Edit Distance with Stiffness Adjustment for Time Series Matching
Framework for Performance Evaluation of Face, Text, and Vehicle Detection and Tracking in Vido: Data, Metrics, and Protocol
Information Geometry for Landmark Shape Analysis: Unifying Shape Representation and Deformation
Principal Angles separate Subject Illumination spaces in YDB and CMU-PIE
High-precision Boundary Length Estimation by Utilizing Gray-Level Information
Statistical Instance-Based Pruning in Ensembles of Independent Classifiers
Camera Displacement via Constrained Minimization of the Algebraic Error
High-Accuracy and Robust Localization of Large Control Markers for Geometric Camera Calibration
These researchers are writing footnotes to Duda and Hart. They are occupying the triple point between numerical methods, applied mathematics, and statistics. It is occassionally lucrative. It paid my wages when I was applying these techniques to look down capability for pulse doppler radar.
The basic architecture of all this research is that the researchers have a monopoly on thinking, mathematics, and writing code and the computers crunch the numbers, both during research and later in a free standing but closed application. There is nothing foomy here.
I’ve got the February issue of the IEEE Transactions on Pattern Analysis and Machine Intelligence lying on my coffee table. Let’s evesdrop on what the professionals are up to
Offline loop investigation for handwriting analysis
Robust Face Recognition via Sparse Representation
Natural Image Statistics and Low-Complexity Feature Selection
An analysis of Ensemble Pruning Techniques Based on Ordered Aggregation
Geometric Mean for Subspace Selection
Semisupervised Learning of Hidden Markov Models via a Homotopy Method
Outlier Detection with the Kernelized Spatial Depth Function
Time Warp Edit Distance with Stiffness Adjustment for Time Series Matching
Framework for Performance Evaluation of Face, Text, and Vehicle Detection and Tracking in Vido: Data, Metrics, and Protocol
Information Geometry for Landmark Shape Analysis: Unifying Shape Representation and Deformation
Principal Angles separate Subject Illumination spaces in YDB and CMU-PIE
High-precision Boundary Length Estimation by Utilizing Gray-Level Information
Statistical Instance-Based Pruning in Ensembles of Independent Classifiers
Camera Displacement via Constrained Minimization of the Algebraic Error
High-Accuracy and Robust Localization of Large Control Markers for Geometric Camera Calibration
These researchers are writing footnotes to Duda and Hart. They are occupying the triple point between numerical methods, applied mathematics, and statistics. It is occassionally lucrative. It paid my wages when I was applying these techniques to look down capability for pulse doppler radar.
The basic architecture of all this research is that the researchers have a monopoly on thinking, mathematics, and writing code and the computers crunch the numbers, both during research and later in a free standing but closed application. There is nothing foomy here.