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70 results for “Convolutional Neural Network (CNN)”

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Review ArticleOpen accessIn the abstractArtificial Intelligence in COVID-19 Management: A Systematic ReviewSamaneh Mohammadi, SeyedAhmad SeyedAlinaghi et al.With the development of modern technologies in the field of healthcare, the use of Artificial Intelligence (AI) in disease management is increasing. AI methods may assist healthcare providers in the COVID-19 era. The current study aimed to observe the efficacy and importance of AI for managing the COVID-19 pandemic. An organized search was conducted, utilizing PubMed, Web of Science, Scopus, … …Journal of Computer Science, Vol. 19, Issue 5 · 30 Mar 2023 · 8,052 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmotion Recognition from Microblog Managing Emoticon with Text and Classifying using 1D CNNMd. Ahsan Habib, M. A. H. Akhand, Md. Abdus Samad KamalMicroblog, an online-based broadcast medium, is a widely used forum for people to share their thoughts and opinions. Recently, Emotion Recognition (ER) from microblogs is an inspiring research topic in diverse areas. In the machine learning domain, automatic emotion recognition from microblogs is a challenging task, especially, for better outcomes considering diverse content. Emoticon becomes very common in the text … …Journal of Computer Science, Vol. 18, Issue 12 · 7 Dec 2022 · 6,921 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutism Detection from 2D Transformed EEG Signal using Convolutional Neural NetworkZahrul Jannat Peya, M. A. H. Akhand, Jannatul Ferdous Srabonee, Nazmul SiddiqueAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder relating to speech complications, nonverbal and social communication, and repetitive behaviors. There is no remedy for ASD but early diagnosis, mediation, and supportive care can aid the development of language, conduct, and communication skills. As the cause of ASD is a neurodevelopmental disorder, its diagnosis based on brain function analyzing different brain … …Journal of Computer Science, Vol. 18, Issue 8 · 31 Jul 2022 · 7,921 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproved Classification Model using CNN for Detection of Alzheimer’s DiseaseRagavamsi Davuluri, Ragupathy RengaswamyAlzheimer’s Disease (AD) is commonly called a neurodegenerative disorder and it is a common form of dementia. There is no permanent cure for this brain disease hence the early diagnosis of such disease using medical imaging system is highly significant. Machine learning models play a vital role in the detection of AD. Since most of the conventional machine learning models … …Journal of Computer Science, Vol. 18, Issue 5 · 30 May 2022 · 6,252 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Model of Bidirectional Long-Short Term Memory and CNN for Multivariate Time Series Classification of Remote Sensing DataSawsan Morkos GharghoryClassification of multivariate time series has got massive attention in the last decade. The traditional modeling classifiers are complicated patterns and are incompetent to capture the dependencies of multivariate time series data. To include both of the effective features and the embedded relationships in the multivariate time series, a new hybrid model which incorporates both Convolutional Neural Network (CNN) and … …Journal of Computer Science, Vol. 17, Issue 9 · 29 Sep 2021 · 6,686 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Literature Review of Software Defect Prediction Using Deep LearningAhmed Bahaa, Enas Mohamed Fathy, Ahmed Sharaf Eldin et al.The approaches associated with software defect prediction are used to reduce the time and cost of discovering software defects in source code and to improve the software quality in the organizations. There are two approaches to reveal the software defects in the source code. The first approach is concentrated on the traditional features such as lines of code, code complexity, … …Journal of Computer Science, Vol. 17, Issue 5 · 22 May 2021 · 10,967 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock price prediction using Generative Adversarial NetworksHungChun Lin, Chen Chen, GaoFeng Huang, Amir JafariDeep learning is an exciting topic. It has been utilized in many areas owing to its strong potential. For example, it has been widely used in the financial area which is vital to the society, such as high-frequency trading, portfolio optimization, fraud detection and risk management. Stock market prediction is one of the most popular and valuable areas in finance. … …Journal of Computer Science, Vol. 17, Issue 3 · 2 Apr 2021 · 17,700 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeafsnapNet: An Experimentally Evolved Deep Learning Model for Recognition of Plant Species based on Leafsnap Image DatasetEmmanuel Adetiba et al.Plants are very important living organisms on earth because humans and animals depend on them for nutrition, oxygen, medicine and balance in the ecosystem. Therefore, plant species recognition is critical to the improvement of agricultural productivity, mitigation of climate change and the discovery of new medicinal plants. However, species recognition has remained a difficult task even for trained botanists, because … …Journal of Computer Science, Vol. 17, Issue 3 · 1 Apr 2021 · 7,956 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Content Filtering from Spam Posts on Social Media using Weighted Multimodal ApproachChastine Fatichah, Wildan F. Lazuardi, Dini A. Navastara et al.The system for filtering spam posts on social media is preferred to obtain the relevant content and expected by users. The previous works on spam detection have been done to filter irrelevant content on email and social media based on text or image separately. Due to the social media posts are commonly in the form of image, text, or both, … …Journal of Computer Science, Vol. 17, Issue 1 · 21 Jan 2021 · 7,904 accessesView PDFCite
Research ArticleOpen accessIn the abstractFine-Tuned MobileNet Classifier for Classification of Strawberry and Cherry Fruit TypesVenkatesh, Nagaraju Yallappa, Siddhanth Udayashankar Hegde, Sangeetha Raj StalinThis paper proposed an accurate, fast and reliable strawberry, cherry fruit detection and classification system for the automated strawberry cherry yield estimation. State-of-the-art deep learning-based fine-tuned MobileNet Convolutional Neural Network is developed to detect and classify strawberry and cherry fruit types in the outdoor field. The proposed CNN model is trained on 4250 strawberry fruit images, 3878 Cherry fruit images … …Journal of Computer Science, Vol. 17, Issue 1 · 20 Jan 2021 · 7,953 accessesView PDFCite