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817 articles for “Classify”
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Visual Features based Paddy Leaf Disease Recognition, its Severity Detection and Remedy Prediction using K-means Clustering and AdaBoost
Abstract: AbstractAgriculture is a vital part of an economy. Paddy is one of the main food crops which play a major role in agricultural field. The gross national income of a country depends on paddy cultivation. But the production of paddy is damaged due to different types of paddy leaf diseases. Generally, farmers and agricultural experts identify diseases manually which is very ineffective and time consuming. So effective recognition, severity detection, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 7, Issue 3, 2020 · pp. 41–52 Read article
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An Analysis on Gender Classification using Face Images Using DWT, (2D)2PCA and SVM
Abstract: AbstractClassifying gender compared to others and is used in this work. Biometry is the use of physical characteristics like face, fingerprints, iris, etc. of an individual for personal identification. Some of the difficult issues of face biometrics are face detection, face recognition, and face identification. These problems are being researched by the computer vision community for the last few decades. Considering the big population, the authentication process of an individual …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 7, Issue 3, 2020 · pp. 30–40 Read article
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Pattern Extraction and Classification of ECG Signals using Neuro-Fuzzy Techniques
Abstract: Electrocardiography is a technique which provides the interpretation of the electrical activity of the heart over a period of time. The condition of cardiac health is given by Electrocardiogram (ECG) and heart rate. This paper represents the techniques, which extracts features from the ECG signals and classify them. ECG signal were taken from preselected data segment of the MIT‐BIH Arrhythmia Database. Pattern extraction provides the PQRST-wave values, heart rate and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 1, Issue 3, 2014 · pp. 1–7 Read article
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Facial Expression Recognition Using Convolutional Neural Network
Abstract: The recognition of facial expression is a key step in nonverbal human communication in the field of computer vision. The Facial Expression Recognition (FER) system reflects emotions as well as mental activities, social interaction with people and expressing positive or negative attitude in general. It has many applications like human machine interaction, understanding human behavior and emotions, mental state identification, drowsiness detection for driving safety and health care. One of …
Published in Journal of Open Source Developments · Vol. 6, Issue 1, 2019 · pp. 18–27 Read article
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Knowledge discovery in software defect datasets using learning algorithms
Abstract: In this paper, the learning impact on various classification models were studied which were built using binary class-imbalanced data. Before the learning process, some preprocessing techniques were applied to training datasets for removing the redundancy. Nowadays feature selection and sampling techniques become an essential tool for many data mining task because learning algorithms do not perform well with defective datasets, dimensionality reduction problem arises. Sampling technique is also used to …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 2, 2018 · pp. 18–26 Read article
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Real-time Malicious URL Detection Using Machine Learning
Abstract: In malicious URLs (universal resource locators)discovery, antiquated classifiers are tested because of the information volume is enormous, designs are dynamical over the long haul, and furthermore the relationships among choices are modern. Feature engineering plays a crucial role in addressing these issues. To raised representation, the underlying the drawback and improve the performances of classifiers in characteristic malicious URLs.This paper proposes a mixture of linear and non-linear house transformation strategies. …
Published in Journal of Web Engineering & Technology · Vol. 8, Issue 1, 2021 · pp. 8–13 Read article
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Semantic Segmentation Using Fully Convolutional Network for An Autonomous Vehicle
Abstract: Numerous individuals inside the profound learning and PC vision networks comprehend what picture arrangement is. We would like to inform about our model that, what single object or scene is present within the image. Semantic segmentation is the most informative segmentation, where we wish to classify each and every pixel within the image. Deep networks have proved to be encoded with highlevel feature like semantic means which can deliver superior …
Published in Recent Trends in Parallel Computing · Vol. 8, Issue 1, 2021 · pp. 21–27 Read article
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Predict the Severity of Diabetes Cases, Using K-Means and Decision Tree Approach
Abstract: In recent years, diabetes has emerged as one of the most prevalent infections, and its prevalence is rapidly increasing globally. Type 2 diabetes is common throughout the world. For the management and prophylaxis of diabetes, early detection is crucial. Machine Learning (ML) approaches are rapidly gaining importance in the field of diagnostic purposes due to their ability to classify data. In this article, a mixed recommended technique is presented to …
Published in Journal of Advances in Shell Programming · Vol. 9, Issue 2, 2022 · pp. 24–31 Read article
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Timely Diabetes Possibility Prediction Using AI Techniques
Abstract: The fastest chronic life-threatening disease affecting more than 422 million people globally is diabetes. The primary causes of type 2 diabetes are lifestyle choices and environmental factors. It is a slowgrowing disease which starts to develop metabolic factors long before they evolve into a disease and is formally diagnosed by a fasting sugar test. There are records of indications related to diabetes from 520 patients in the dataset that was …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 2, 2022 · pp. 37–47 Read article
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Automated Brinjal Leaf Disease Detection Using Machine Learning: A Sri Lankan Study
Abstract: The spread of plant diseases has a significant negative impact on agricultural output quality and yield, resulting in significant economic losses. Plant disease automation in agricultural science is our country's main concern due to the economic crisis and the emphasis on organic farming practices. Furthermore, the accuracy and efficiency of recognizing sick leaves have increased due to the expanding usage of smart technology. This study uses machine learning and image …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 3, 2022 · pp. 41–56 Read article
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Identification of Handwritten Digits using Machine Learning
Abstract: Handwritten Digit Recognition is one of the practical issues in sample recognition applications. The task for handwritten recognition has been difficult due to various variations in written styles. The capacity to create an effective algorithm that can detect handwritten numbers given by users via a scanner, tablet, and other digital devices is at the core of the issue. Artificial intelligence is used in machine learning, which automatically corrects errors based …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 1, 2023 · pp. 19–26 Read article
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Groundwater Quality and Its Suitability Assessment for Irrigation and Drinking in Different Aquifers of Faridpur, Bangladesh
Abstract: Abstract Thirty five groundwater samples were collected to appraise the chemical constituents in order to classify them on the basis of their suitability for irrigation and drinking. The considered water quality parameters are pH, EC, TDS, calcium, magnesium, sodium, potassium, iron, manganese, boron, sulphate, bicarbonate, chloride, sodium adsorption ratio, residual sodium carbonate, soluble sodium percentage, Kelly’s ratio, magnesium percentage and hardness. All the water samples were neutral to slightly alkaline …
Published in Journal of Water Pollution & Purification Research · Vol. 2, Issue 3, 2015 · pp. 5–14 Read article
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Hand Geometry based Person Identification System using Support Vector Machine
Abstract: In recent times, it is immensely important to identify a person to access the secure data in a system. In this case, verification and identification techniques play a vital role to secure the process. Password system has failed to provide such kind of security. We highly emphasize on the biometric characteristics to design such secured systems. In this paper, we provide a way to identify a unique person by his …
Published in Current Trends in Signal Processing · Vol. 5, Issue 1, 2015 · pp. 26–33 Read article
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Knowledge-based, Automated Land Use/Land Cover Mapping Using Resourcesat-1 AWiFS
Abstract: The availability of large quantity of data from high-resolution space-based sensors along with the existing archives surpassed our ability to extract information from all the data using supervised image analysis techniques. Hence there is a need for automated image classifier with high throughput. Knowledge-based, modular, hierarchical decision-based classifier suitable for the analysis and extraction of major land use/land cover classes from IRS Resourcesat AWiFS data has been developed and the …
Published in Journal of Remote Sensing & GIS · Vol. 3, Issue 1, 2012 · pp. 11–20 Read article
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Effect of Image Band Number and Band Multicollinearity on Mapping Accuracy of Tree Diversity and Evenness
Abstract: 800x600 Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Satellite imageries are increasingly being used in the studies of plant diversity due to cost effective wider spatial coverage. Multispectral or hyperspectral imageries consist of different spectral bands where some bands might be multicollineared among them and deemed redundant to use in the classification/analysis. This study investigates how the accuracies of maps of tree diversity and evenness of an area …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 2, 2013 · pp. 14–22 Read article
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Effect of Rank Based Correlation on K-Nearest Neighbour
Abstract: AbstractBecause of its simplicity, higher efficiency and effectiveness, K-nearest neighbour (KNN) isthe most popular and chosen algorithm in the last few years. It has many conveniences withthe exception of some inconvenience. In this study, we explore the correlation and dependencebetween attributes, and try to significantly improve the classification accuracy from existingalgorithm by skipping correlated attributes. To get classification accuracy, we applied thisskipping correlated attributes method in KNN ranking based classifier. …
Published in Current Trends in Information Technology · Vol. 7, Issue 2, 2017 · pp. 17–22 Read article
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Crop Recommendation System Using AI
Abstract: For agriculturists, the online application is useful. In recent few years, experts have become increasingly focused on solid land readiness and its strategy for a variety of reasons. The developing income for agribusiness land and soil thriving evaluation, as well as the strength of the soil, areimportant goals for improving the mark of combination of the examination area. Assessment of the health of the soil and the land, with its …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 13, Issue 1, 2023 · pp. 1–8 Read article
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Land Use/Land Cover Change Detection Using GIS and Remote Sensing: A Case Study of District Rawalpindi
Abstract: Aggregation and visualization of geographic data are significant aspects of environment modeling, agricultural management and socio-economic status. Geographical Information System (GIS) and Remote Sensing had been used to aggregate the change detection of land use/Land cover (LULC) change. This can help to identify adaptations in the properties or phenomena which are imaginary in the diverse time period. This study takes the temporal-spatial subtleties of LULC using satellite imageries of different …
Published in Journal of Remote Sensing & GIS · Vol. 10, Issue 2, 2019 · pp. 19–34 Read article
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Brain Tumor Detection Using an Artificial Neural Network in MRI Images
Abstract: MRI is the widely used imaging technique in the biomedical field for the detection, diagnosis and evaluation of brain tumors. The large structural variability among brain tumor makes detection of a challenging problem. The medical problems are severe, if the tumor is detected at the later stage. Hence, diagnosis is necessary at the earliest. In this work, a neural network classifier is used for the detection of tumors from the …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 5, Issue 1, 2018 · pp. 14–22 Read article
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Change Detection of Land Use/Land Cover using Geospatial Techniques: A Case Study of Narpala Mandal, Anantapur District, Andhra Pradesh, India
Abstract: The present study depicts an integrated approach of Geospatial techniques like Remote Sensing (RS) and Geographical Information System (GIS) for assessment of Land Use Land Cover changing aspects of Narpala Mandal of Anantapur district, AP, India. The temporal data of two different years of Landsat imagery of 2008 and 2018 were acquired by USGS Earth Explorer and Land use Land cover changes in the Narpala mandal for 2008 and 2018 …
Published in Journal of Remote Sensing & GIS · Vol. 10, Issue 2, 2019 · pp. 6–12 Read article