35 results for machine learning
Showing 1–20 · 2.69 seconds · RSS
-
Journal Article
Classification of grapevine cultivars using Kirlian camera and machine learning
…acquired coronas of the berries with numerical parameters and used machine learning algorithms to classify grapevine cultivars. We tested this method on eight grapevine cultivars, performing different tests. The results show that coronas of grapevine berries contain useful information about…
-
Journal Article
Electromyogram based muscle stress estimation of Gastrocnemius medialis using Machine learning algorithms
…of gastrocnemius medialis without and with a workout (exercise) using machine learning algorithms. Ten healthy subjects (Seven male & three female) have been chosen on the basis of their age, height and mass. The experiment has been conducted without a workout and with a workout having a set of 10…
-
Journal Article
Machine learning-based landslide susceptibility assessment for shallow landslide mitigation in the Gumitir Mountain Area, Indonesia
Recurrent rainfall-induced landslides in Gumitir, East Java, threaten the Jember–Banyuwangi route. This study aims to develop mitigation strategies by analyzing influencing factors and predicting landslide-prone areas using logistic regression and random forest models. A dataset consisting of 96…
From your institution’s collections
- Machine learning dan computational intelligenceWidodo Budiharto · 2016 · UNILAK
- Machine learning (konsep dan implementasi)Yaya Heryadi · 2020 · UNILAK
-
Journal Article
Carpet Back Sizing Quality Assessment by Measuring the Amount of Resin Using Image Processing and Machine Learning Approaches
…of the carpet are controlled by the operator touching the carpet on the machine carpet finishing line or manually while rolling the carpet. Proposed in this paper is an automatic method based on the evaluation of the bending stiffness of the sized carpet that uses digital image processing and…
-
Journal Article
Spatial Transfer Learning for Cross-Regional Crop Mapping
…change. Advances in Earth observation, satellite data availability, and machine learning (ML) have enabled effective large-scale crop monitoring. However, traditional crop mapping approaches rely on large labeled datasets, which are often costly and difficult to obtain, motivating the use of…
-
Journal Article Full text
The Prediction of Yarn Elongation of Kenyan Ring-Spun Yarn using Extreme Learning Machines (ELM)
…were tested under standard testing conditions. Cotton lint parameters, machine parameters and yarn elongation were used to design yarn elongation prediction models. The elongation prediction models used three network training algorithms, including backpropagation (BP), an extreme learning machine…
-
Journal Article
INTELLIGENT HYBRID OPTIMIZATION OF WEDM FOR Ti-6Al-4V USING TAGUCHI DEEP LEARNING AND ANOVA FOR ENHANCED SURFACE INTEGRITY AND PREDICTION ACCURACY
…(Ra). Experimental trials conducted on an ELECTRONICA Sprintcut 734 WEDM machine, utilizing deionized water and a 0.5 mm brass wire electrode, revealed that Ton was the most dominant factor, contributing 38.02 % to the Ra variation, followed by the Ton-Toff interaction (27.80 %), while Toff (7.28…
-
Journal Article
Strojno učenje in umetna inteligenca v pametnih izdelovalnih sistemih
Artificial intelligence and machine learning are increasingly shaping the development of modern smart manufacturing systems, where reliable and efficient operation is strongly dependent on accurate awareness of machine states and process conditions. In this paper, the practical applicability of…
-
Journal Article
Uporaba umetne inteligence pri končni kontroli kvalitete elektromotorjev
…dependence on specialist knowledge. To address these limitations, several machine learning approaches are discussed, including ensemble-based classification models, transfer learning, and deep neural networks. The application of ensemble models enables automatic feature selection and implicit…
-
Journal Article Full text
Comparison of tree-based classification algorithms in mapping burned forest areas
In this study, we compared the performance of tree-based classification algorithms – Random Forest (RF), Rotation Forest (RotF), J48, The Alternating Decision Tree (ADTree), Forest by Penalising Attributes (Forest PA), Logical Analysis of Data Algorithm (LADTree) and Functional Trees (FT) – for…
-
Journal Article Full text
Change detection work-flow for mapping changes from arable lands to permanent grasslands with advanced boosting methods
The necessity of mapping changes in land cover categories based on satellite imageries is a challenging task especially in terms of arable land and grasslands. The phenological phases of arable lands change quickly while grasslands is more stable. It might be hard to capture these changes regarding…
-
Journal Article Full text
Predicting tree species based on the geometry and intensity of aerial laser scanning point cloud of treetops
Based on the laser point clouds of 240 individual trees that were also identified in the field, we developed decision trees to distinguish deciduous and coniferous trees and individual tree species: Picea abies, Larix decidua, Pinus sylvestris, Fagus sylvatica, Acer pseudoplatanus, Fraxinus…
-
Journal Article
Cross-lingual transfer of sentiment classifiers
…for multiple languages. Cross-lingual embeddings can be used to transfer machine learning models between languages, thereby compensating for insufficient data in less-resourced languages. We use cross-lingual word embeddings to transfer machine learning prediction models for Twitter sentiment…
-
Journal Article
Tagging Named Entities in Croatian Tweets
Named entity extraction tools designed for recognizing named entities in texts written in standard language (e.g., news stories or legal texts) have been shown to be inadequate for user-generated textual content (e.g., tweets, forum posts). In this work, we propose a supervised approach to named…
-
Journal Article Full text
Uporaba strojnega učenja za določitev poplavljenih območij – primer poplav v Selški dolini leta 2007 : Application of data mining for determination of flooded areas – Selška valley 2007 floods case study
…flooded areas even in very large areas. To determine the flooded areas, machine learning techniques were applied to different input data. SPOT satellite image (multispectral and panchromatic), NDVI index, relief and its derivatives (altitude, slope, curvature), distance from rivers and land use…
-
Journal Article
The Metamorphosis of Polyphemus's Gaze in Marij Pregelj's Painting (1913-1967)
…the rosette of a cathedral, which changes into a human figure, a washing machine door, a meat grinder's orifice, a blind “windeye” or window, and so on. The themes of his final two paintings, which he, already more than a year before his boding senseless death at the age of 54, executed but did not…
-
Journal Article
Die disruptive Kraft in klassenräumen oder über die KI-unterstützten Tools beim Fremdsprachenlehren und -lernen
…property, data protection, and the actual impact of AI-assisted learning. Beyond these challenges, it is worth highlighting, exploring, and, above all, exploiting the potential of AI-based tools and the potential and constructive use of these tools in and for foreign language teaching. In the…
-
Journal Article
IDENTIFICATION OF THE DAMAGE TYPES FOR REINFORCED CONCRETE USING CNN MODELS
Monitoring reinforced concrete structures makes it possible to prevent their further destruction, thereby significantly reducing the cost of their maintenance. Machine learning excels in precisely identifying and classifying various types of damage. The convolutional neural network, constructed…
-
Journal Article
Uporaba metod strojnega učenja za preučevanje odnosov med značilnostmi branik in okoljem
…In our study, (multiple) linear regression (MLR) with four nonlinear machine learning methods are compared: artificial neural networks (ANN), model trees (MT), bagging of model trees (BMT) and random forests of regression trees (RF). To compare the different regression methods, four datasets were…
-
Journal Article
Monitoring changes in urban green spaces using Sentinel 2 data, a case study from Vietnam
…Vietnam from 2016 to 2024 in a 4-year cycle, using Sentinel-2 images and machine learning algorithms. Sentinel-2 multi-temporal data were used to calculate spectral indices including NDVI, NDWI, NDBI, BUI and SAVI. Next, the study used two machine learning algorithms, Random Forest (RF) and Support…