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17 results for “MLP classification”
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Research ArticleOpen accessEvery word in the titleArabic Sentiment Classification using MLP Network Hybrid with Naive Bayes AlgorithmMohammad Subhi Al-Batah, Shakir Mrayyen, Malek AlzaqebahSentiment analysis has recently become one of the growing areas of research related to text mining and natural language processing. Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. Most of the current studies related to this topic focus mainly on English … …Journal of Computer Science, Vol. 14, Issue 8 · 7 Aug 2018 · 9,273 accessesView PDFCite
Research ArticleOpen accessIn the keywordsChronic Lung Disease Identification in Chest CT Scans Through Hybrid Deep Transfer Learning FrameworkGarima Jain, Amit Kumar Goel, Rahul KumarAccurate and timely diagnosis is essential for successful treatment of chronic pulmonary conditions, particularly lung tumours. To capture more complicated pathological characteristics, diagnostic algorithms based on current data sets are restricted to using older databases and single branch systems. This research introduces a new solution: A hybrid deep learning model applied to a recently released quantitative database of CT scans … …Journal of Computer Science, Vol. 22, Issue 8 · 9 Sep 2026 · 651 accessesView PDFCite
Research ArticleOpen accessIn the keywordsImproving the Detection of Mask-Wearing Mistakes by Deep LearningChahinez Mérièm BentaouzaThis study focuses on the detection of wearing mask errors after machine learning by a Multi-Layer Perceptron Mixer (MLP Mixer) applied to protect masks from COVID-19. To combat the spread of the COVID-19 pandemic, facemasks have become an essential accessory, so it's necessary to identify individuals who follow this health protection. In this case, the most successful face-detection method Viola-Jones … …Journal of Computer Science, Vol. 20, Issue 7 · 25 Apr 2024 · 5,195 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEffect of Hidden Layer Neurons on the Classification of Optical Character Recognition Typed Arabic NumeralsNidal F. Shilbayeh, Mahmoud Z. IskandaraniProblem statement: The effect of varying the number of nodes in the hidden layer and number of iterations are important factors in the recognition rate. In this paper, a novel and effective criterion based on Cross Pruning (CP) algorithm is proposed to optimize number of hidden neurons and number of iterations in Multi Layer Perceptron (MLP) neural based recognition system. … …Journal of Computer Science, Vol. 4, Issue 7 · 31 Jul 2008 · 7,556 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDesign of a Neural Networks Classifier for Face DetectionF. Smach, M. Atri, J. Mitéran, M. AbidFace detection and recognition has many applications in a variety of fields such as security system, videoconferencing and identification. Face classification is currently implemented in software. A hardware implementation allows real-time processing, but has higher cost and time to-market. The objective of this work was to implement a classifier based on neural networks MLP (Multi-layer Perception) for face detection. The … …Journal of Computer Science, Vol. 2, Issue 3 · 31 Mar 2006 · 6,885 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAutomated Breast Cancer Diagnosis based on GVF-Snake Segmentation, Wavelet Features Extraction and Neural Network ClassificationAbderrahim Sebri, Jihène Malek, Rached TourkiBreast cancer accounts for the second most cancer diagnoses among women and the second most cancer deaths in the world. In fact, more than 11000 women die each year, all over the world, because this disease. The automatic breast cancer diagnosis is a very important purpose of medical informatics researches. Some researches has been oriented to make automatic the diagnosis … …Journal of Computer Science, Vol. 3, Issue 8 · 31 Aug 2007 · 7,407 accessesView PDFCite
Research ArticleOpen accessIn the abstractEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 912 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Fraud Detection Methods in Banking Using Machine Learning TechniquesYoussef Tounsi, Ennouri TaziFraud detection in banking requires algorithms that balance classification performance, computational efficiency, and regulatory interpretability, criteria that are rarely benchmarked together. We present a comprehensive evaluation of nine machine learning approaches (Logistic Regression, Decision Tree, Random Forest, SVM, SGD, XGBoost, CatBoost, LightGBM, and MLP) across three datasets differing in size, imbalance severity, and feature type (synthetic, real-world PCA-anonymized, and large-scale … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,341 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing Bias Detection in Tweets Using Bayesian Probabilistic ModelPrasanth G Rao, Harsha Chigurupati, Krish Hashia et al.Content moderation on social media faces persistent challenges from inconsistent evaluation shaped by subjective judgment and subtle semantic variations. This work proposes a Bayesian probabilistic framework for detecting bias in tweets using WordNet-based vocabulary filtering, statistical normalization via z-scores, and threshold optimization. The system is stateless, scalable, and dataset-agnostic, requiring no session-specific information. Unlike complex models such as Support Vector … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,009 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of Multi-Layer Perceptron in Ensemble Using Random Search for Bankruptcy PredictionBambang Siswoyo, Zuraida Abal Abas, Ahmad Naim Che Pee et al.A corporation is in financial trouble if it has money problems but has yet to be bankrupt. Companies' financial woes must be identified early to implement various bankruptcy avoidance strategies. This study discusses the optimization of the multi-layer perceptron ensemble stacking classifier hyperparameter by majority voting as a methodology for constructing a classification model for bankruptcy prediction (MLP-STM). The primary … …Journal of Computer Science, Vol. 19, Issue 2 · 5 Feb 2023 · 7,229 accessesView PDFCite