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149 articles for “Neural Network Classification”
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Research ArticleOpen accessAll words, across the recordAssessing Bi-LSTM Model’s Performance in Identifying AI Generated Text in Digital MediaTinashe Crispen Garidzira, William Tichaona Vambe, Courage MatoboboThe rapid growth of AI-generated content from ChatGPT, Gemini, and many others poses significant challenges in digital media. There are increasing instances of text generated by machine learning models being indistinguishable from human-written text. This calls for an effective way of detecting and distinguishing text generated by AI from human text. Using a Cross-Industry Standard Process for Data Mining (CRISP-DM) … …Journal of Computer Science, Vol. 21, Issue 8 · 8 Oct 2025 · 2,416 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAutomating Paddy Crop Disease Classification With Deep Learning ModelsShiva Shankar J, S. Palanivel, S. China VenkateswarluRice is a staple food crop for more than 10 countries. High consumption of rice demands better yield of crop. Timely disease diagnosis in paddy is fundamental to preventing yield losses and ensuring an adequate supply of rice for a rapidly rising worldwide population. Agriculture and modern farming is one of the fields where IoT and automation can have a … …Journal of Computer Science, Vol. 21, Issue 8 · 1 Sep 2025 · 5,696 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,099 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordPhishing Website Detection Using Improved Multilayered Convolutional Neural NetworksHadia Bibi, Syed Rehan Shah, Mirza Murad Baig et al.The internet has become an essential part of many fields: Communication, entertainment, commerce, industrial production, agriculture, etc. Unfortunately, online users are vulnerable to various attacks; this could lead to financial damages and loss of personal information. Phishing is seen as an internet threat and a cybercrime where anyone can capture personal information and data by posing as a reliable source. … …Journal of Computer Science, Vol. 20, Issue 9 · 6 Jul 2024 · 6,578 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordClassification of Thoracic X-Ray Images of COVID-19 Patients Using the Convolutional Neutral Network (CNN) MethodRamacos Fardela, Dian Milvita, Mawanda Almuhayar et al.Recently, radiology modalities have been widely used to detect COVID-19. Thoracic X-rays and CT scans are the primary radiological tools utilized in the diagnosis and treatment of individuals with COVID-19. In addition, chest CT scans are more accurate and sensitive in early COVID-19 identification. A new problem arises in diagnosing the results of CT scan images of COVID-19 by radiologists … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 5,753 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordQuantization and Pipelined Hardware Implementation of Deep Neural Network ModelsEl Hadrami Cheikh Tourad, Mohsine EleuldjInrecent years, Deep Neural Networks (DNNs) have garnered much interest due toadvances in computational power and data availability. Indeed, DNNs presents a considerable advantage in several challenges, suchas classification problems and video analysis. Although, such accomplishmentleads to significantly increasing energy demands, computational expenses, andmemory capacity. In addition, current efficient DNNs may have more complex andextensive structures. As a result, implementing … …Journal of Computer Science, Vol. 18, Issue 11 · 26 Oct 2022 · 5,703 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Comprehensive Review on Skin Cancer Detection Strategies using Deep Neural NetworksAkepati Sankar Reddy, Gopinath M. PSkincancer is a deadly malignancy. Incomplete D.N.A. repair in skin cells causeshereditary mutations and cancer. Early skin cancer is easier to treat since itspreads slowly to other body areas. As a result, the optimal time to find it isduring its infancy. Because of the rising frequency of skin cancer, the highmortality rate, and the high cost of medical treatment, early … …Journal of Computer Science, Vol. 18, Issue 10 · 5 Oct 2022 · 6,400 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordClassifications of Skull Fractures using CT Scan Images via CNN with Lazy Learning ApproachMd Moniruzzaman Emon, Tareque Rahman Ornob, Moqsadur RahmanClassification of skull fracture is a challenging task for both radiologists and researchers. Skull fractures result in broken pieces of bone, which can cut into the brain and cause bleeding and other injury types. So it is vital to detect and classify the fracture very early. In real world, often fractures occur at multiple sites. This makes it harder to … …Journal of Computer Science, Vol. 18, Issue 3 · 15 Mar 2022 · 9,005 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordPhonocardiogram Classification Based on Machine Learning with Multiple Sound FeaturesKhalid M.O. Nahar, Obaida M. Al-Hazaimeh, Ashraf Abu-Ein, Nasr GharaibehIn this study the heartbeat sound signals were tackled by classifying them into heart disease categories such as normal, artifact, murmur and extrahals in an attempt for early detection of heart defects. Phonocardiogram (i.e., PCG) is used to obtain the digital recording dataset of the heart sounds using an electronic stethoscope or mobile device. Multiple features are extracted from the … …Journal of Computer Science, Vol. 16, Issue 11 · 26 Nov 2020 · 8,259 accessesView PDFCite
Review ArticleOpen accessAll words, across the recordDeep Learning Approach for Human Action Recognition Using Gated Recurrent Unit Neural Networks and Motion AnalysisNeziha Jaouedi, Noureddine Boujnah, Med Salim BouhlelHuman action recognition is a computer vision task. The evaluation of action recognition algorithms relies on the proper extraction and learning of the data. The success of the deep learning and especially learning layer by layer led to many imposing results in several contexts that include neural network. Here the Recurrent Neural Networks (RNN) with hidden unit has demonstrated advanced … …Journal of Computer Science, Vol. 15, Issue 7 · 29 Jul 2019 · 8,018 accessesView PDFCite