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210 results for “Deep Q-Network”
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Research ArticleOpen accessIn the abstractGoogleNet CNN Neural Network towards Chest CT-Coronavirus Medical Image ClassificationNesreen Alsharman, Ibrahim JawarnehIn the end of the year 2019 and the beginning of the year 2020, the world was overwhelmed by a medical pandemic that was not previously seen which is known Covid-19 (Coronavirus). Coronavirus (CoV) is a large family of viruses that cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS-CoV) and … …Journal of Computer Science, Vol. 16, Issue 5 · 14 May 2020 · 9,519 accessesView PDFCite
Research ArticleOpen accessIn the abstractMethodology to Analyze the Stability of Bench Marks Applied for Settling Measurements of Buildings FoundationAndréa de Seixas, José Roberto de SeixasIn this work, one type of vertical bench mark is presented for the realization of the Vertical Local Geodetic Network for the control and analysis of settling foundation elements. The revision of the previous norm NBR 6122/96 to the current norm NBR 6122/2010, contributed in Brazil to the obligation of the services of measurement of settlings in buildings with more … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 1 · 18 Mar 2020 · 7,150 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,077 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Pre-Processing Techniques to Improve DBT Classification Accuracy With CNN ResNet-50Qodri Aziz, Slamet Riyadi et al.Digital Breast Tomosynthesis (DBT) is a three-dimensional imaging technology that is meant to determine breast cancer more accurately than regular mammograms. But low contrast and noise can make DBT images less clear, which can make deep learning-based classification less accurate. This study seeks to assess the impact of diverse preprocessing techniques on breast cancer classification outcomes utilizing the ResNet-50 Convolutional … …Journal of Computer Science, Vol. 22, Issue 10 · 21 Oct 2026 · 419 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Soft Voting Ensemble of XGBoost and DNN for At-Risk Student Performance PredictionEugene Wan, Po Chan Chiu, Mohammad bin Hossin et al.Early identification of at-risk students in higher education is important for timely academic intervention, yet conventional prediction methods often struggle with data imbalance and limited model precision. This study proposes a hybrid soft voting ensemble model that integrates Extreme Gradient Boosting (XGBoost) and Deep Neural Network (DNN) to enhance multi-class student grade prediction (A-F classification) and at-risk student identification. This … …Journal of Computer Science, Vol. 22, Issue 5 · 28 May 2026 · 1,404 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,043 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Super-Resolution using Auto-Encoders with Parallel Skip-ConnectionsLisha Pulickal Purushothaman, Jayasree Vadakke KadangoteSuper-resolutionimages are highly desired when employed for numerous analytical purposes andobviously because of their superior attractive visual effect. To create aHigh-Resolution (HR) image from one or more Low-Resolution (LR) images, animage super-resolution technique is used. When dealing with naturalenvironments and settings, it is not always easy to access high-resolutionimages. The main barriers to the same are limitations in acquisition methods.In … …Journal of Computer Science, Vol. 18, Issue 11 · 11 Nov 2022 · 6,084 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Approach to Develop, Assess and Optimize Energy Consumption Models for Air-Cooled Chillers using Machine Learning AlgorithmsMostafa Tahmasebi, Nabil NassifThe building sector accounts for more than 70% of the total electricity use. Chillers consume more than 50% of electrical energy during seasonal periods of building use. With the growth of the building sector and climate change, it's essential to develop energy-efficient HVAC systems that optimize the ever-increasing energy demand. This study aims to develop an energy consumption prediction model … …American Journal of Engineering and Applied Sciences, Vol. 15, Issue 3 · 8 Nov 2022 · 5,520 accessesView PDFCite
Research ArticleOpen accessIn the abstractLong Short-Term Memory Model for Classification of English-PtBR Cross-Lingual Hate SpeechThiago D. Bispo, Hendrik T. Macedo, Flávio de O. Santos et al.Automatic and accurate recognition of hate speech is a difficult job. In addition to the inherent ambiguity of the natural language, deep understanding of the linguistic structure is imperative. Usually, discriminatory discourse does not make use of typical expressions and often abuse of sarcasm. Good knowledge of world and assessment of context are thus highly demanded. Several approaches have been … …Journal of Computer Science, Vol. 15, Issue 10 · 1 Nov 2019 · 7,343 accessesView PDFCite
Research ArticleOpen accessIn the abstractFarmer-Friendly Mobile Application for Automated Leaf Disease Detection of Real-Time Augmented Data Set using Convolution Neural NetworksRishiikeshwer B. S., T. Aswin Shriram, J. Sanjay Raju et al.In farming, crops are prone to a wide variety of diseases. The impact of sudden climatic change has adverse effects on their growth, providing incubation to harmful viruses and bacteria. Diseases to crops imply a significant negative impact on health, economy and livelihood of the human population. According to the data from the Food and Agricultural Organization (FAO), an average … …Journal of Computer Science, Vol. 16, Issue 2 · 24 Aug 2019 · 8,993 accessesView PDFCite