E
Electronic design automation (EDA), GPU computing status
341–342
Electronic structure propagation
basic problem
59–61
building blocks and implementation
65–68
calculations
69–72
density matrix
69
Fock matrix
69
hardware considerations
69
matrix operations
66–68
overview
59
technology basics
61–65
Electron microscopy (EM), brain connectivity reconstruction
axon surface visualization
795–797
core methods
793–797
future work
811–812
GPU active ribbon segmentation
797–802
GPU-based volume brick filtering
802–803
GPU implicit surface ray casting
797
GPU volume brick boundary detection
803–809
HistogramVoxelSweep algorithm
804–805
implementation
797–809
level set re-distancing
801–802
level set updating
797–800
on-demand volume filtering
796
performance analysis
809–811
semiautomatic axon segmentation
793–795
3D axon tracking
802
3D volume visualization
795–797
Embedded speed-limit-sign recognition
compute power adjustments
511–512
fast-radial symmetry
505–506
feature-based pipeline
499–501
FFT correlation with nonlinear filters
507
future work
513–514
implementation
505–507
methods
499–505
overview
497–498
pipeline evaluation
508–511
pipeline scalability
512–513
recognition results
508
results
507–513
SIFT-based pipeline
505
template-based pipeline
500–505
Energy consumption, Katsevich CT image reconstruction parallelization
674–675
Enumeration scheme, classifier cascades
541
Error-correcting codes, multiclass SVM
295
Euler method
black hole simulations
105
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