Search Results - (( using convolutional network algorithm ) OR ( pattern classifications using algorithm ))
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1
Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. …”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…Based on investigation different architecture and parameter, the suitable deep learning model has been presented to get optimize best result and testing time. To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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3
Gender Classification: A Convolutional Neural Network Approach
Published 2016“…An approach using a convolutional neural network (CNN) is proposed for real-time gender classification based on facial images. …”
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4
Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network
Published 2021“…Using the Grad- CAM algorithm, we showed how the proposed saliency map shifted the model attention to the relevant region in chest radiograph images. …”
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5
Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion
Published 2017“…In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. …”
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Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel
Published 2024“…Several imaging, computer vision, and pattern recognition algorithms are employed to describe five dermoscopic features. …”
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Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network
Published 2021“…Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network
Published 2021“…Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. …”
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9
Converged Classification Network For Matching Cost Computation
Published 2020“…This paper focused on matching cost computation step as an initial step to produce the disparity or depth map. The proposed convolutional neural network designed with the output neurons in the classification part scaled-downin converging style. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq
Published 2024“…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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11
Maize leaf disease detection and classification using Convolutional Neural Network (CNN) / Syafiqah Amir
Published 2023“…The dataset used in this project consist of 800 images of four category of leaf achieved 90 percent of accuracy by using the CNN algorithm.…”
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Diabetic Retinopathy Detection Model using Hybrid of U-Net and Vision Transformer Algorithms
Published 2024“…Now, we present a hybrid model which is a combination of U-Net algorithm used for image segmentation and Vision Transformer for classification. …”
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13
An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA
Published 2025“…However, these algorithms often fall short in consistently detecting and classifying network intrusions, particularly when distinctions between classes are subtle or when facing evolving attack patterns. …”
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14
Finger-Vein Biometric Identification Using Convolutional Neural Network
Published 2016“…A novel approach using a convolutional neural network (CNN) for finger-vein biometric identification is presented in this paper. …”
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15
Underwater Image Recognition using Machine Learning
Published 2024“…A Convolutional Neural Network (CNN) is a type of a deep learned an algorithm that has been created for image processing when using convolutional layers to automatically and in a hierarchical way learn features from the input images. …”
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16
Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…The leaf features are first learned directly from the raw representations of input data using Convolutional Neural Networks (CNN), and then the chosen features are exploited based on a Deconvolutional Network (DN) approach. …”
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17
Adaptive Feature Selection and Image Classification Using Manifold Learning Techniques
Published 2024“…Dimension reduction is the field of interest and demand of many data analysts and is widely used in computer vision, image processing, pattern recognition, neural networks, and machine learning. …”
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Postal address handwritten recognition using convolutional neural network / Nur Hasyimah Abd Aziz
Published 2020“…Therefore, this study will develop handwritten recognition system by using Convolutional Neural Network (CNN) as a classifier. …”
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19
Enhancing land cover classification in remote sensing imagery using an optimal deep learning model
Published 2023“…By leveraging the abilities of Deep Neural Networks (DNNs) namely, Convolutional Neural Networks (CNN) or Recurrent Neural Networks (RNN), the technology can autonomously learn spatial and spectral features inherent to the RSI. …”
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Analyzing RNA-Seq gene expression data using deep learning approaches for cancer classification
Published 2022“…In the last phase, classification is performed, and eight DL algorithms are used. …”
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