Use of machine learning for classification of sand particles
Particle classification is essential for geotechnical engineering practice since particle shapes correlate with the mechanical and hydraulic properties of sand layers. Traditional shape classification is tedious, subjective, and time-consuming because it depends on manual visual comparison with reference particles. This study demonstrates …
Classification of Sand Using Deep Learning — NYU Scholars
The results demonstrate that sand classification using a larger number of sand types resulted in a lower classification accuracy. Classification accuracy of individual particles achieved using CNN were 10%-15% better than those achieved using NN. CNN can automatically and adaptively learn the spatial hierarchy of features which is superior to ...
Comparison of feature selection and classification for …
Introduction: In the classification of Mass Spectrometry (MS) proteomics data, peak detection, feature selection, and learning classifiers are critical to classification accuracy. To better understand which methods are more accurate when classifying data, some publicly available peak detection algorithms for Matrix assisted Laser Desorption …
How to classify sand types: A deep learning approach
The sand type classification performed in the previous section utilized grayscale images that contain information on the surface texture (degree of contrast-homogeneity within a particle) and contrast within sand particles as well as particle shape (i.e., boundary morphology between sand particles and black-colored background). ...
A Tentative Classification of Sand Dunes Its Application to …
Following is a basic classification of simple dunes which is at the same time genetic and naturalistic. It is based on the assumption that the sand-moving wind blows with unvarying direction. Simple Dunes A. Bare Surfaces or Loose Sand I. The barcan dune. An isolated bare-sand hill on a nonsandy base II. The transverse dune series.
How to classify sand types: A deep learning approach
Abstract. While the identification of sand type helps naturally approximate physical and mechanical properties, it is challenging to judge sand types without prior information. This study attempts to identify the sand type in 2D grayscale images by using convolutional neural networks (CNNs). Six different sand samples with high geometric ...
Revised Soil Classification System: Implementation and …
Current soil classification systems capture early efforts to understand soil behavior and properties. Most classification systems recognize the central role of particle size d because it determines the balance between particle-level forces. Capillary and/or electrical forces gain relevance and control fabric formation when the grain size is less …
M. R. Smith and L. Collis (eds): Aggregates: sand, gravel
The first part of the chapter explains aggregate potential of igneous, metamorphic, and sedimentary rocks and geologic occurrences of sand and gravel …
"Sand Types": A New Physicochemical Classification of Sand …
Hence, a new physicochemical classification ("Sand Types") of sand that falls in the "sand fields" of SSC plots pertaining to two famous authors is being proposed. …
Optimum selection of sand control method using a …
After selection of best sand control method by applying MCDM, DOE and Response Surface Methodology (RSM) are used to optimize the parameters of the best-selected sand control method. DOE is a powerful technique to gain maximum information from a data set with the minimum number of experiments. In this regard, Full Factorial …
Classification of Sand Using Deep Learning — NYU Scholars
The work demonstrates that computer vision has a remarkable ability to automatically classify 64% of individual sand particles among 20 types of sand, the accuracy for sand …
Feature Selection and Extreme Learning Machine Tuning by Hybrid Sand
@inproceedings{Stankovic2022FeatureSA, title={Feature Selection and Extreme Learning Machine Tuning by Hybrid Sand Optimization Algorithm for Diabetes Classification}, author={Marko Stankovic and Neboj{vs}a Ba{vc}anin and Miodrag Zivkovic and Dijana Jovanovic and Milos Antonijevic and Milos Bukmira and Ivana Strumberger}, …
Detection of sand dunes on Mars using a regular vine-based
The dune classification (or detection) problem (DCP) we deal with consists of identifying the presence or absence of sand dunes from remotely sensed images of the surface of Mars. In order to solve this problem, support vector machines [10] and random forests (RF) [13] were used with good results in [14]. Here, we propose a different …
Predicting USCS soil classification from soil property variables …
USCS classification is based in part on particle-size distribution, but also includes consideration of organic matter content and the soil plasticity as defined by the Atterberg limits (liquid limit and plastic limit). USCS considers all particle sizes, including gravel (>4.76 mm), sand (4.76 mm-0.074 mm), and silt and clay (<0.074 mm). 3.
'Sand Types': A new physico-chemical classification of sand …
The economic viability of sand in the construction industry depends on its size, shape, shell content, etc. It is imperative to understand the proportions of sand sub-classes and shell content in ...
How to classify sand types: A deep learning approach
This paper presents a CNN-based classification framework to identify sand types from 2D images. The potential features of sand particles indicate the intrinsic …
(PDF) Classification and diversity of perennial sand
The classification of Serbian sand-dune vegetation and the status of the described associations has not been validated by numerical analyses. ... In the process of data selection and sand y ...
Advancements in Soil Classification: An In-Depth Analysis of …
Soil texture refers to the size and proportion of sand, silt, and clay particles in ... The implementation procedure begins with the model selection phase of the soil classification procedure. The selection of a model is a critical factor in determining its feasibility for deployment on a resource-constrained device since it directly affects ...
Specifications for and Classification of Brick
Brick selection is made according to the specific application in which the brick will be used. Standards for brick cover specific uses of brick and classify the brick by performance characteristics. The performance criteria include strength, durability and aesthetic requirements. Selection of the proper specification and classification within that
Feature selection for improved classification accuracy targeting
Request PDF | Feature selection for improved classification accuracy targeting riverine sand mapping | Regular monitoring of riverine sand is crucial for its sustainable management. Towards ...
Classification of sandy coastlines
Only sedimentary coastlines, which are characterised by the presence of loose sediments on the shoreface and on the beach, will be included in the following rough classification. There are 5 main types of coasts defined by the angle of incidence of the prevailing waves. Type 1: Perpendicular wave approach, angle of incidence close to zero.
An improved breast cancer classification with hybrid chaotic sand …
The drawbacks of traditional methods are addressed by the inclusion of the hybrid feature selection technique known as chaotic sand optimization with the Remora optimization algorithm. ... (2023). Efficient feature selection for breast cancer classification using soft computing approach: A novel clinical decision support system. Multimedia ...
IJGI | Free Full-Text | Feature Extraction and Selection of …
The concept of the local climate zone (LCZ) has been recently proposed as a generic land-cover/land-use classification scheme. It divides urban regions into 17 categories based on compositions of man-made structures and natural landscapes. Although it was originally designed for temperature study, the morphological structure …
Detection and classification of an object buried in sand
Request PDF | On Jan 1, 2007, D. Déultot and others published Detection and classification of an object buried in sand by an acoustic resonance spectrum method | Find, read and cite all the ...
Detection of sand dunes on Mars using a regular vine-based
Sand dune mapping was the early focus of aeolian geomorphologists, and continued progress has been made in refining classification schemes and developing advanced classification techniques.
Dams: Classification, Choice and Selection of Site
The availability of sand and gravel (for concrete) near the dam site would reduce the cost of a concrete dam. Spillway is a major part of any dam and its size and type and the natural restrictions in its location will affect the selection of the type of dam. Spillway requirements are decided by the runoff and stream-flow characteristics.
Types of Sand: Uses, Properties, Grain size
Followings are the classification of Sand: Based on the grain size of the particle, sand is classified as Fine Sand (0.075 to 0.425mm), …
Binary Sand Swarm Optimization Algorithm for Wrapper …
Therefore, feature selection is an effective pre-processing step intended to enhance the classification performance by choosing a small number of relevant or significant features. It is important to note that due to the NP-hard characteristics of feature selection, the search agent can become trapped in the local optima, which is extremely ...
Determination of shape parameters of sands: a deep …
This study explores the feasibility of predicting the shape parameters of sand particles via a well-trained deep learning model. Over 7000 sand particle images from …
Classification of Sand Using Deep Learning | Journal of …
The work demonstrates that computer vision has a remarkable ability to automatically classify 64% of individual sand particles among 20 types of sand, the …