6 hasil untuk "Samreen Naeem"
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Artikel Jurnal Teks lengkap
An Unsupervised Machine Learning Algorithms: Comprehensive Review
Machine learning (ML) is a data-driven strategy in which computers learn from data without human intervention.The outstanding ML applications are used in a variety of areas.In ML, there are three types of learning problems: Supervised, Unsupervised, and Semi-Supervised Learning.Examples of…
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The Classification of Medicinal Plant Leaves Based on Multispectral and Texture Feature Using Machine Learning Approach
This study proposes the machine learning based classification of medical plant leaves. The total six varieties of medicinal plant leaves-based dataset are collected from the Department of Agriculture, The Islamia University of Bahawalpur, Pakistan. These plants are commonly named in English as…
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Artikel Jurnal
Machine learning approach for the classification of corn seed using hybrid features
Seed purity is an important indicator of crop seed quality. On the other side, corn is an important crop of the modern agricultural industry with more than 40% grain Worldwide production. The purpose of this study was to examine the feasibility of a machine learning (ML) approach for classifying…
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Artikel Jurnal
Machine Learning Based Statistical Analysis of Emotion Recognition using Facial Expression
Background: Humans can deliver many emotions during a conversation. Facial expressions show information about emotions. Objectives: This study proposed a Machine Learning (ML) approach based on a statistical analysis of emotion recognition using facial expression through a digital image…
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Artikel Jurnal Teks lengkap
Machine-Learning Based Hybrid-Feature Analysis for Liver Cancer Classification Using Fused (MR and CT) Images
The purpose of this research is to demonstrate the ability of machine-learning (ML) methods for liver cancer classification using a fused dataset of two-dimensional (2D) computed tomography (CT) scans and magnetic resonance imaging (MRI). Datasets of benign (hepatocellular adenoma, hemangioma…
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Artikel Jurnal Teks lengkap
Machine Learning Based Automated Segmentation and Hybrid Feature Analysis for Diabetic Retinopathy Classification Using Fundus Image
The object of this study was to demonstrate the ability of machine learning (ML) methods for the segmentation and classification of diabetic retinopathy (DR). Two-dimensional (2D) retinal fundus (RF) images were used. The datasets of DR—that is, the mild, moderate, non-proliferative, proliferative…