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spatial_gan

Spatial Generative Adversarial Networks

spatial_transformer_networks

Implementation of spatial transformer networks in keras 2.0 using tensorflow 1.0 as backend.

spearmint

Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Larochelle and Ryan P. Adams. Advances in Neural Information Processing Systems, 2012

specio

specio: Python input/output for spectroscopic files

spectral

Python module for hyperspectral image processing

spectral-1

spectral-angular-classification-of-satellite-image

A software package is built for display and classification of Hyperspectral Images captured byIMS-1 HySI sensor has been developed using SAM.The construction and display of the 3-D cube by considering all the 64 bands of image at a time. The identification of classes in the Hyperspectral Image using a supervised classification algorithm called the Spectral Angle Mapper Algorithm. Results are obtained to read and reorganize multiple 2-D datasets into a single compact 3D dataset cube.Thematic Information Extraction — Supervised Classification Remotely sensed data may be analyzed to extract use- ful thematic information. This transforms the data into in- formation. For example, themes may include land-cover, water bodies, and clouds. The classification may be per- formed using supervised, unsupervised and fuzzy set clas- sification approaches. In a supervised image classification, the identity and lo- cation of some of the land-cover types should be known beforehand through a combination of fieldwork, analy- sis of aerial photography, maps, and personal experience. The analyst attempts to locate sites in the remotely sensed data that represent homogeneous examples of these known land-cover types. These areas are commonly referred to as training sites because the spectral characteristics of these known areas are used to train the classification algorithm for eventual land-cover mapping of the remainder of the image. Multivariate statistical parameters such as means, standard deviations, and covariance matrices are calculated for each training site. Every pixel both inside and outside these training sites is then evaluated and assigned to the class where it has the highest likelihood of being a mem- ber. This is often referred to as hard classification because a pixel is assigned to only one class (e.g., forest), even though the sensor records the radiant flux from a mixture of biophysical materials, for example: 10% bare soil, 20% scrub shrub, 70% forest.

spectral-library-reader

C++ Library that reads the splib06a file, which is a custom binary spectral reflectance database file created by USGS

spectral-tool

Development of a led-arduino-camera system for hyperspectral imaging

spectral_motion

A Hyperspectral Visualization and Analysis Engine for iOS

spectral_unmixing

CLI utilities to perform linear spectral unmixing of Hyperspectral images based on spectral signature of pure endmembers.

spectralmask

Hyperspectral skin masking/segmentation (single-pass, line-by-line)

spectrolab

:exclamation: This is a read-only mirror of the CRAN R package repository. spectrolab — Class and Methods for Hyperspectral Data. Homepage: https://github.com/annakat/spectrolab

specvis-good-gpu

SpecVis - Visualization and classification of 2D chemical and hyperspectral images.

spglm

spice

Sparsity Promoting Iterated Constrained Endmembers

spikedetection

Spike detection

spiking-net-tensorflow

Example simulation of spiking networks in Tensorflow adapted from a Matlab example

spiking-neural-networks-with-cellular-automaton

A research project for treating neural networks as cellular automata (an alternative to lstm)

spint

splatnet

SPLATNet: Sparse Lattice Networks for Point Cloud Processing (CVPR2018)

splayer

Automatically exported from code.google.com/p/shooter-player

splot

Lightweight plotting for geospatial analysis in PySAL

spp

Sparsity Preserving Projection, a feature extraction algorithm in Pattern Recognition area

spp_net

SPP_net : Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

sptendecomp

Tensor decomposition with directed factor level sparity

spup

R package: spup - Spatial Uncertainty Propagation Analysis

spuq

Spectral methods for Uncertainty Quantification

spvcm

multilevel spatially-correlated variance components models

spyder

Official repository for Spyder - The Scientific PYthon Development EnviRonment