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46 results for “input vector”
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Research ArticleOpen accessIn the keywordsSelf-Generation ART-1 Neural Network with Gradient-Descent Method Aid for Latin Alphabet RecognitionMbaïtiga ZacharieProblem statement: In this study a self-generation ART-1 neural network that is an efficient algorithm that emulates the self-organizing pattern recognition developed to avoid the stability-plasticity dilemma in competitive networks learning, is presented for Latin alphabet recognition to use in a vision system for road sings recognition. Approach: The first step of our approach deals with the training process where … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,566 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Approach to Head positioning using Fixed Center Interpolation Net with Weight Elimination AlgorithmMahmoud Zaki IskandaraniA reliable algorithm for head movements inside a vehicle is designed. The proposed algorithm allowed the adjustment of basic functions such as indicators, mirrors and reverse lights based on the driver final head position. The algorithm system mapped a predefined coordinates for driver’s head that resulted in a computable geometry via a sensory system which is fed to the vehicle … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,305 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuel Prediction Model for Driving Patterns Using Machine Learning TechniquesManjunath TK, Ashok Kumar PSIn recent years, the demand for fuel efficiency has become a crucial aspect of the automotive industry. Predicting fuel economy accurately is essential for optimizing vehicle performance and reducing environmental impact. This proposed model presents a machine learning-based approach for developing a fuel prediction model using the real dataset. The model aims to predict fuel efficiency for different drivers by … …Journal of Computer Science, Vol. 20, Issue 3 · 29 Jan 2024 · 5,480 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutism Spectrum Disorder Prediction Using Hybrid Deep Learning Model and a Recommendation System Application for Autistic PatientBiplov Paneru, Bishwash Paneru, Krishna Bikram Shah et al.The goal of this study is to create machine learning models that use a big dataset to predict Autism Spectrum Disorder (ASD). To achieve optimal performance, a number of algorithms were employed and refined, including Support Vector Machines (SVM), Random Forest, XGBoost, Multi-Layer Perceptron (MLP) and a hybrid model that combines MLP and SVM. To evaluate the durability of the … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,219 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomated Medical Image Captioning with Soft Attention-Based LSTM Model Utilizing YOLOv4 AlgorithmPaspula Ravinder, Saravanan SrinivasanThe medical image captioning field is one of theprominent fields nowadays. The interpretation and captioning of medical imagescan be a time-consuming and costly process, often requiring expert support. Thegrowing volume of medical images makes it challenging for radiologists tohandle their workload alone. However, addressing the issues of high cost andtime can be achieved by automating the process of medical image … …Journal of Computer Science, Vol. 20, Issue 1 · 16 Dec 2023 · 6,651 accessesView PDFCite
Research ArticleOpen accessIn the abstractArabic Poetry Authorship Attribution using Machine Learning TechniquesAl-Falahi Ahmed, Ramdani Mohamed, Bellafkih MostafaIn this study, authorship attribution in Arabic poetry will be conducted to determine the authorship of a specified text after documents with recognized authorships have been allocated. This work also measures the impact performance of Naïve Bayes, Support Vector Machine and Linear discriminant analysis for Arabic poetry authorship attribution using text mining classification. Several features such as lexical features, character … …Journal of Computer Science, Vol. 15, Issue 7 · 27 Jul 2019 · 150,975 accessesView PDFCite
Research ArticleOpen accessIn the abstractSymbolic Aggregate approXimation-Local Binary Pattern Feature Descriptor Combination for Automatic Facial Expression RecognitionSumithra M.D., M. Abdul RahimanAutomatic identification of facial expression is a significant research area which is anticipated for real time processing in Human-Computer Interaction domain. Along with an efficient classifier for assigning the class label to each of the input face image, it is very necessary to have a strong feature vector for training the classifier. This paper proposes an effectual combination of Local … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 7,513 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Method of Long Short-Term Memory and Auto-Encoder Architectures for Sarcasm DetectionMohammed M. AL-Ani, Nazlia Omar, Ahmed Adil NafeaSarcasm detection is considered one of the most challenging tasks in sentiment analysis and opinion mining applications in the social media. Sarcasm identification is therefore essential for a good public opinion decision. There are some studies on sarcasm detection that apply standard word2vec model and have shown great performance with word-level analysis. However, once a sequence of terms is being … …Journal of Computer Science, Vol. 17, Issue 11 · 1 Dec 2021 · 7,187 accessesView PDFCite
Research ArticleOpen accessIn the abstractMissing Values Treatment and Feature Reduction Analysis to Enhance ClassificationD. Muralidharan, K. Renuka, Mulagala Jaswant et al.Datasets may have large number of features which makes it hard and time consuming to classify. Additionally, they may have irrelevant and noise features too with missing values. The missing values should be treated in a proper way so that the classifier accuracy can be improved. There is also a need to reduce features and select only the features necessary … …Journal of Computer Science, Vol. 16, Issue 2 · 20 Feb 2020 · 8,114 accessesView PDFCite
Research ArticleOpen accessIn the abstractFusion of Features and Extreme Learning Machine for Facial Expression RecognitionBayezid Islam, Arfat HossainHuman emotion is highly correlated to facial expressions. Due to its growing demand in different sectors, an emotion recognition method is proposed through recognizing facial expressions. The input image is preprocessed and then the resulting image is segmented into four facial expression regions following the newly proposed segmentation method. Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) are … …Journal of Computer Science, Vol. 15, Issue 12 · 28 Dec 2019 · 7,404 accessesView PDFCite