Search Results - (( _ location based algorithm ) OR ( image classification learning algorithms ))*
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…Another structure of MLP trained using backpropagation algorithm is used to detect and locate the base of the young corn tree using the skeleton of the segmented image. …”
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Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm
Published 2020“…This paper presented an analysis performance of deep learning object detector by combining a deep learning Convolutional Neural Network (CNN) for object classification and applies classic object detection algorithms to devise our own deep learning object detector. …”
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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The first algorithm locates interest points in food images using an MSER. …”
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Breast cancer histological images nuclei segmentation and optimized classification with deep learning
Published 2022“…A breast cancer multi-classification technique based on a suggested deep learning algorithm was examined to achieve the accuracy of 99.2% using a huge database of ICIAR 2018, demonstrating the method’s efficacy in offering an important weapon for breast cancer multi-classification in a medical setting. …”
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A Comparative of Two-Dimensional Statistical Moment Invariants Features in Formulating an Automated Probabilistic Machine Learning Identification Algorithm for Forensic Application
Published 2023“…Moreover, the proposed identification algorithm is also tested in different scenarios, including based on the classification of strength association measurements between the extracted feature sets. …”
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Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak
Published 2020“…Towards achieving better detection in real-time environment, colour pixel-based images were trained on five pre-trained CNNs using transfer learning algorithm. …”
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Machine-learning guided fracture density seismic inversion: A new approach in fractured basement characterisation
Published 2020“…A machine learning algorithm of well log fracture density - borehole image log (BHI) guided seismic inversion was performed. …”
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The impact of the combat method on radiomics feature compensation and analysis of scanners from different manufacturers
Published 2024“…After harmonization with the Combat algorithm, the distributions of radiomic features were aligned in terms of location and scale. …”
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Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”
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Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin
Published 2005“…In order to have a system which has an ability to learn, back-propagation learning algorithm is used. …”
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Automated feature extraction on brain MRI images for predicting multiple sclerosis patient disability
Published 2022“…From the large-scale features, a correlation analysis is performed to select the highly correlated features used for predicting patients’ disability. This was based on machine learning and regression algorithms at the first phase. …”
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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification
Published 2024Subjects:Conference Paper -
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…The locations of landslides were detected accurately by employing two Machine learning classifiers, namely, SVM and RF, decision rule and hierarchal rules sets were developed by applying decision tree (DT) algorithm to provide improved landslide inventory. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…The key metrics for the evaluation are classification accuracy, classification precision and classification recall. 855 images were used to train and test the algorithms. …”
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Advances in remote sensing technology, machine learning and deep learning for marine oil spill detection, prediction and vulnerability assessment
Published 2020“…The Support Vector Machine (SVM) and Artificial Neural Network (ANN) are the most used machine learning algorithms for oil spill detection, although the restriction of ML models to feed forward image classification without support for the end-to-end trainable framework limits its accuracy. …”
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Classification of brain tumors: using deep transfer learning
Published 2023“…Experimenters employed data augmentation and learning algorithms.…”
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