Developing And Testing A Combined Image Masking And Image Classification Procedure For Large Area Vegetation Mapping

2005 ◽  
Author(s):  
D.R. Millar ◽  
J.G. Morrice ◽  
P.L. Whitworth ◽  
R.V. Birnie
Keyword(s):  
Image Classification ◽  
Vegetation Mapping ◽  
Large Area ◽  
Classification Procedure

scholarly journals AN ALGORITHM OF FUZZY INFERENCE SYSTEM FOR ISAR IMAGE CLASSIFICATION

2017 ◽  
Vol 2 ◽  
pp. 154
Author(s):  
Krasimir Slavyanov ◽  
Chavdar Minchev
Keyword(s):  
Neural Network ◽  
Image Classification ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Information Analysis ◽  
Simulation Experiments ◽  
Inference System ◽  
Classification Procedure ◽  
Neural Network Simulation ◽  
Mamdani Fuzzy Inference System

This article offers an original ISAR image classification procedure based on Mamdani fuzzy inference system (FIS) dedicated to compute multiple results each from different type of analyzing criteria. The modeling and information analysis of the FIS are developed to draw a general conclusion from several results each produced by classification from neural network. Simulation experiments are carried out in MATLAB environment.

scholarly journals Direct, ECOC, ND and END Frameworks—Which One Is the Best? An Empirical Study of Sentinel-2A MSIL1C Image Classification for Arid-Land Vegetation Mapping in the Ili River Delta, Kazakhstan

2019 ◽  
Vol 11 (16) ◽  
pp. 1953 ◽  
Author(s):  
Alim Samat ◽  
Naoto Yokoya ◽  
Peijun Du ◽  
Sicong Liu ◽  
Long Ma ◽  
...  
Keyword(s):  
Random Forest ◽  
Land Cover ◽  
Image Classification ◽  
Landsat Imagery ◽  
Vegetation Mapping ◽  
River Delta ◽  
Arid Land ◽  
Superior Performance ◽  
Sentinel 2A ◽  
Vegetation Species

To facilitate the advances in Sentinel-2A products for land cover from Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat imagery, Sentinel-2A MultiSpectral Instrument Level-1C (MSIL1C) images are investigated for large-scale vegetation mapping in an arid land environment that is located in the Ili River delta, Kazakhstan. For accurate classification purposes, multi-resolution segmentation (MRS) based extended object-guided morphological profiles (EOMPs) are proposed and then compared with conventional morphological profiles (MPs), MPs with partial reconstruction (MPPR), object-guided MPs (OMPs), OMPs with mean values (OMPsM), and object-oriented (OO)-based image classification techniques. Popular classifiers, such as C4.5, an extremely randomized decision tree (ERDT), random forest (RaF), rotation forest (RoF), classification via random forest regression (CVRFR), ExtraTrees, and radial basis function (RBF) kernel-based support vector machines (SVMs) are adopted to answer the question of whether nested dichotomies (ND) and ensembles of ND (END) are truly superior to direct and error-correcting output code (ECOC) multiclass classification frameworks. Finally, based on the results, the following conclusions are drawn: 1) the superior performance of OO-based techniques over MPs, MPPR, OMPs, and OMPsM is clear for Sentinel-2A MSIL1C image classification, while the best results are achieved by the proposed EOMPs; 2) the superior performance of ND, ND with class balancing (NDCB), ND with data balancing (NDDB), ND with random-pair selection (NDRPS), and ND with further centroid (NDFC) over direct and ECOC frameworks is not confirmed, especially in the cases of using weak classifiers for low-dimensional datasets; 3) from computationally efficient, high accuracy, redundant to data dimensionality and easy of implementations points of view, END, ENDCB, ENDDB, and ENDRPS are alternative choices to direct and ECOC frameworks; 4) surprisingly, because in the ensemble learning (EL) theorem, “weaker” classifiers (ERDT here) always have a better chance of reaching the trade-off between diversity and accuracy than “stronger” classifies (RaF, ExtraTrees, and SVM here), END with ERDT (END-ERDT) achieves the best performance with less than a 0.5% difference in the overall accuracy (OA) values, but is 100 to 10000 times faster than END with RaF and ExtraTrees, and ECOC with SVM while using different datasets with various dimensions; and, 5) Sentinel-2A MSIL1C is better choice than the land cover products from MODIS and Landsat imagery for vegetation species mapping in an arid land environment, where the vegetation species are critically important, but sparsely distributed.

scholarly journals Effectively Diagnosing Malaria by Optimizing the Hyperparameters of CNN using Genetic Algorithm on the Multi core GPU

2020 ◽  
Vol 8 (6) ◽  
pp. 2983-2991
Keyword(s):  
Genetic Algorithm ◽  
Image Classification ◽  
Deep Neural Network ◽  
State Of The Art ◽  
Testing Time ◽  
Large Area ◽  
Training Time ◽  
Time Period ◽  
Testing Accuracy ◽  
Selection Of

Image classification is an important task in computer vision involving a large area of applications such as object detection, localization and image segmentation. When it comes to image classification, the most adopted methods are based on deep neural network and especially convolutional Neural Networks(CNN). Selection of hyperparameters plays a crucial role in performance of model and it comes by experience. So, in this paper, we will use the genetic algorithm(GA) to automate and build the CNN model for higher accuracy on GPU which is provided by Google Collaboratory cloud. The best architecture of CNN after several generations of the genetic algorithm is then compared to the state-of-the-art CNN. We have used the malaria cell images dataset to find out whether the person is normal or if they are suffering from malaria. We trained two types of malaria cells, which are uninfected and parasitized on Tesla P100 multi core GPU. We got a high training accuracy of 97% and got a testing accuracy of about 95% on the multicore GPU that boosted the speed of execution of training time period and testing time period.

scholarly journals A System for Object Detection and Image Classification on Photographic Plates

1984 ◽  
Vol 78 ◽  
pp. 133-135 ◽  
Author(s):  
M.L. Malagnini ◽  
M. Pucillo ◽  
P. Santin ◽  
G. Sedmak ◽  
G.L. Sicuranza
Keyword(s):  
Object Detection ◽  
Image Classification ◽  
Central Processor ◽  
Research Projects ◽  
Classification Procedure ◽  
Specific Research ◽  
Reasonable Amount ◽  
Objective Classification

AbstractA system for detecting and classifying (faint) astronomical objects on photographic plates is presented. The system is planned to perform all the main operations, from the digitization of the plates with a PDS lOlOA microdensitometer up to the final classification, under the control of the VAX-11/750 central processor. The aim of the project is to obtain an objective classification and reliable description of large amounts of objects, in a reasonable amount of time,for specific research projects. The detection and classification procedure is organized in modules, each of which is general enough to be applied to different kinds of analyses and to different classes of objects, according to astronomical requirements. An example of application to the problem of star/galaxy discrimination is given.

Convergent Beam Electron Diffraction

1978 ◽  
Vol 36 (3) ◽  
pp. 304-315
Author(s):  
G. Lehmpfuhl
Keyword(s):  
Electron Diffraction ◽  
Diffraction Pattern ◽  
Crystal Surface ◽  
Diffraction Spot ◽  
Crystal Thickness ◽  
Large Area ◽  
Electron Microscopic ◽  
Additional Information ◽  
Microscopic Investigations

Introduction In electron microscopic investigations of crystalline specimens the direct observation of the electron diffraction pattern gives additional information about the specimen. The quality of this information depends on the quality of the crystals or the crystal area contributing to the diffraction pattern. By selected area diffraction in a conventional electron microscope, specimen areas as small as 1 µ in diameter can be investigated. It is well known that crystal areas of that size which must be thin enough (in the order of 1000 Å) for electron microscopic investigations are normally somewhat distorted by bending, or they are not homogeneous. Furthermore, the crystal surface is not well defined over such a large area. These are facts which cause reduction of information in the diffraction pattern. The intensity of a diffraction spot, for example, depends on the crystal thickness. If the thickness is not uniform over the investigated area, one observes an averaged intensity, so that the intensity distribution in the diffraction pattern cannot be used for an analysis unless additional information is available.

TEM Study of a Tilt Boundary in Hot-Pressed Silicon

1981 ◽  
Vol 39 ◽  
pp. 160-161
Author(s):  
C. B. Carter ◽  
J. Rose ◽  
D. G. Ast
Keyword(s):  
Electron Diffraction ◽  
Imaging Technique ◽  
Interface Structure ◽  
Large Area ◽  
Weak Beam ◽  
Lattice Fringe ◽  
Electron Diffraction Technique ◽  
Tilt Boundaries ◽  
Beam Technique ◽  
Twist Boundaries

The hot-pressing technique which has been successfully used to manufacture twist boundaries in silicon has now been used to form tilt boundaries in this material. In the present study, weak-beam imaging, lattice-fringe imaging and electron diffraction techniques have been combined to identify different features of the interface structure. The weak-beam technique gives an overall picture of the geometry of the boundary and in particular allows steps in the plane of the boundary which are normal to the dislocation lines to be identified. It also allows pockets of amorphous SiO2 remaining in the interface to be recognized. The lattice-fringe imaging technique allows the boundary plane parallel to the dislocation to be identified. Finally the electron diffraction technique allows the periodic structure of the boundary to be evaluated over a large area - this is particularly valuable when the dislocations are closely spaced - and can also provide information on the structural width of the interface.

P20 phosphor on polyimide as a large area high-resolution transmission screen for slow scan CCD systems

1995 ◽  
Vol 53 ◽  
pp. 20-21
Author(s):  
C. C. Ahn ◽  
S. Karnes ◽  
M. Lvovsky ◽  
C. M. Garland ◽  
H. A. Atwater ◽  
...  
Keyword(s):  
Mechanical Stability ◽  
High Energy ◽  
Practical Implementation ◽  
Line Pair ◽  
Modulation Transfer ◽  
Large Area ◽  
Ccd Imaging ◽  
Transmission Electron ◽  
The One ◽  
Beam Broadening

The bane of CCD imaging systems for transmission electron microscopy at intermediate and high voltages has been their relatively poor modulation transfer function (MTF), or line pair resolution. The problem originates primarily with the phosphor screen. On the one hand, screens should be thick so that as many incident electrons as possible are converted to photons, yielding a high detective quantum efficiency(DQE). The MTF diminishes as a function of scintillator thickness however, and to some extent as a function of fluorescence within the scintillator substrates. Fan has noted that the use of a thin layer of phosphor beneath a self supporting 2μ, thick Al substrate might provide the most appropriate compromise for high DQE and MTF in transmission electron microcscopes which operate at higher voltages. Monte Carlo simulations of high energy electron trajectories reveal that only little beam broadening occurs within this thickness of Al film. Consequently, the MTF is limited predominantly by broadening within the thin phosphor underlayer. There are difficulties however, in the practical implementation of this design, associated mostly with the mechanical stability of the Al support film.

Study of Tip-Surface Interactions in Scanning Tunneling Microscopy (STM) by Reflection Electron Microscopy (REM)

1990 ◽  
Vol 48 (1) ◽  
pp. 320-321
Author(s):  
W. Lo ◽  
J.C.H. Spence ◽  
M. Kuwabara
Keyword(s):  
High Resolution ◽  
Elastic Strain ◽  
Tunneling Current ◽  
Surface Damage ◽  
Surface Interactions ◽  
Graphite Surface ◽  
Scanning Tunneling ◽  
Large Area ◽  
Tunneling Microscopy ◽  
High Resolution Tem

Work on the integration of STM with REM has demonstrated the usefulness of this combination. The STM has been designed to replace the side entry holder of a commercial Philips 400T TEM. It allows simultaneous REM imaging of the tip/sample region of the STM (see fig. 1). The REM technique offers nigh sensitivity to strain (<10−4) through diffraction contrast and high resolution (<lnm) along the unforeshortened direction. It is an ideal technique to use for studying tip/surface interactions in STM.The elastic strain associated with tunnelling was first imaged on cleaved, highly doped (S doped, 5 × 1018cm-3) InP(110). The tip and surface damage observed provided strong evidence that the strain was caused by tip/surface contact, most likely through an insulating adsorbate layer. This is consistent with the picture that tunnelling in air, liquid or ordinary vacuum (such as in a TEM) occurs through a layer of contamination. The tip, under servo control, must compress the insulating contamination layer in order to get close enough to the sample to tunnel. The contaminant thereby transmits the stress to the sample. Elastic strain while tunnelling from graphite has been detected by others, but never directly imaged before. Recent results using the STM/REM combination has yielded the first direct evidence of strain while tunnelling from graphite. Figure 2 shows a graphite surface elastically strained by the STM tip while tunnelling (It=3nA, Vtip=−20mV). Video images of other graphite surfaces show a reversible strain feature following the tip as it is scanned. The elastic strain field is sometimes seen to extend hundreds of nanometers from the tip. Also commonly observed while tunnelling from graphite is an increase in the RHEED intensity of the scanned region (see fig.3). Debris is seen on the tip and along the left edges of the brightened scan region of figure 4, suggesting that tip abrasion of the surface has occurred. High resolution TEM images of other tips show what appear to be attached graphite flakes. The removal of contamination, possibly along with the top few layers of graphite, seems a likely explanation for the observed increase in RHEED reflectivity. These results are not inconsistent with the “sliding planes” model of tunnelling on graphite“. Here, it was proposed that the force due to the tunnelling probe acts over a large area, causing shear of the graphite planes when the tip is scanned. The tunneling current is then modulated as the planes of graphite slide in and out of registry. The possiblity of true vacuum tunnelling from the cleaned graphite surface has not been ruled out. STM work function measurements are needed to test this.

Illumination from Large Area Light Sources—II

1914 ◽  
Vol 77 (1988supp) ◽  
pp. 82-83
Author(s):  
Herbert E. Ives
Keyword(s):  
Light Sources ◽  
Large Area
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