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40 results for “Pre-Trained Model”

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Research ArticleOpen accessIn the abstractHematologic Cancer Cell Detection and Classification Using Optimized VGG-19 with Stratified K-fold Cross-ValidationHema Patel, Himal Shah, Gayatri Patel, Atul PatelThe most prevalent pediatric blood malignancy is acute lymphoblastic leukemia (ALL). ALL is a lethal disease in which patients have a lower survival rate. Its prompt detection and precise categorization are essential for successful treatment. Manual microscopic diagnosis is laborious, prone to mistakes, and heavily reliant on specialized knowledge. With stratified 7-fold cross-validation, which assures an equal ratio of normal … …Journal of Computer Science, Vol. 21, Issue 11 · 24 Dec 2025 · 1,822 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybridized BERT-Based Approach for Crime News Collection and Classification from Online NewspapersAshour Ali, Shahrul Azman Mohd Noah, Lailatul Qadri Zakaria, Saeed Amer Al AmeriCrime news analysis is crucial for understanding criminal activity, enhancing public safety, and informing policy decisions. The exponential growth and unstructured nature of online news articles, however, present significant challenges for efficient and accurate information extraction. This study aims to enhance the efficiency and accuracy of crime news data collection and classification through advanced Natural Language Processing (NLP) techniques and … …Journal of Computer Science, Vol. 21, Issue 9 · 16 Oct 2025 · 2,297 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Arabic Comments to Detect Cyberbullying from Social Media Using Convolutional Neural Network and Meta-LearningSarah Mansour Elgaud, Mustafa Ali Abuzaraida, Abdullah AlshehabAs a result of the proliferation of social media, cyberbullying has become widespread in the Arab community on social media and cyberbullying has become a concern targeting individuals and may cause some serious side effects. The problems of Natural Language Processing (NLP) for the Arabic language and its complexity make it difficult to classify texts accurately. In recent years, deep … …Journal of Computer Science, Vol. 21, Issue 3 · 10 Feb 2025 · 6,288 accessesView PDFCite
Research ArticleOpen accessIn the abstractScalable and Advanced Framework for Hate Speech Detection on Social Media Using BERT and GPT-2 through Encoder and Decoder ArchitecturesUsman, Nabeela Hasan, Syed Mohammad Khurshid QuadriHate speech is a major problem on social media platforms. Every day, numerous instances of hateful behavior based on race, ethnicity, religion, or gender are witnessed on social media. Most of the leading social media platforms like Instagram, Facebook, Twitter Reddit, etc., have strong community guidelines that condemn and restrict the exchange of hateful language/content in any form. Despite the … …Journal of Computer Science, Vol. 21, Issue 3 · 7 Feb 2025 · 7,333 accessesView PDFCite
Research ArticleOpen accessIn the abstractEthioLSocMDMTLM: Exploring Application of Topic Modeling for Building Ethiopian Language Social Media Data-Based Multilingual Transformer Language Models for Multilingual Hateful Content DetectionNaol Bakala Defersha, Kula Kekeba Tune, Solomon Teferra AbateThis study proposes topic modeling techniques to develop Ethiopian Language Social Media Data Based Multilingual Transformer Language Models for multilingual hateful content detection. We modified various multilingual pretrained models, investigated the challenges of using pre-trained transformer language models, and built multilingual hateful content detection models. Topic words with rows of 1561, 70, and 1044 extracted from Afaan Oromo, Tigrigna, and … …Journal of Computer Science, Vol. 21, Issue 2 · 31 Dec 2024 · 5,217 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Postoperative Brain MRI Segmentation with Automated Skull Removal and Resection Cavity AnalysisSobha Xavier P., Sathish P. K., Raju G.Brain tumors present a significant medical challenge, often necessitating surgical intervention for treatment. In the context of postoperative brain MRI, the primary focus is on the resection cavity, the void that remains in the brain following tumor removal surgery. Precise segmentation of this resection cavity is crucial for a comprehensive assessment of surgical efficacy, aiding healthcare professionals in evaluating the … …Journal of Computer Science, Vol. 20, Issue 5 · 19 Mar 2024 · 5,699 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Mental Health Counseling Conversation Using Natural Language ProcessingSaad Ahmed, Sidrah Khurshid, Muhammad Imran et al.One of the most significant public health challenges of our day is mental illness. Despite the benefits of psychotherapy and counseling, our understanding of conducting effective counseling conversations has been limited due to a lack of high-quality data with labeled results. This research presents a quantitative analysis of relatively good-quality data scraped from an online counseling forum. The dataset comprises … …Journal of Computer Science, Vol. 20, Issue 3 · 29 Jan 2024 · 5,860 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Transfer Learning Approach for Student Attendance System During the COVID-19 PandemicSlimane Ennajar, Walid BouarifiMarking students' attendance has been a challenge during the COVID-19 pandemic. It is a time-consuming task due to the abnormally high number of students present during a learning session; many studies have been proposed to improve the system. However, there are still issues with each of these systems; we have employed deep transfer learning techniques using six pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 3 · 16 Jan 2024 · 6,018 accessesView PDFCite
Research ArticleOpen accessIn the abstractImprovement of Moroccan Dialect Sentiment Analysis Using Arabic BERT-Based ModelsGhizlane Bourahouat, Manar Abourezq, Najima DaoudiThis study addresses the crucial task of sentiment analysis in natural language processing, with a particular focus on Arabic, especially dialectal Arabic, which has been relatively understudied due to inherent challenges. Our approach centers on sentiment analysis in Moroccan Arabic, leveraging BERT models that are pre-trained in the Arabic language, namely AraBERT, QARIB, ALBERT, AraELECTRA, and CAMeLBERT. These models are … …Journal of Computer Science, Vol. 20, Issue 2 · 27 Dec 2023 · 6,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractCustomized Named Entity Recognition Using Bert for the Social Learning Management System Platform CourseNetworkingKayal Padmanandam, KVN Sunitha, Behafarid Mohammad Jafari et al.Named Entity Recognition (NER) is an information extraction task and one of the most researched applications to extract knowledge from massive data. Conventional NER systems identify predefined entities like name, person, location, organization, time, etc. However, there is a limitation to identifying user-defined entities that are specific to an application. This challenge introduces the concept of customized NER. For instance, … …Journal of Computer Science, Vol. 20, Issue 1 · 15 Dec 2023 · 6,991 accessesView PDFCite