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63 results for “capture effect”
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Research ArticleOpen accessIn the abstractRobust Adversarial Attack Detection via Generative Adversarial Network With Residual Multi-Layer Aggregation Based Contrastive Loss FunctionAmudha Gopalakrishnan, Nalini JosephAdversarial attacks in medical imaging refer to subtle modifications to images that mislead diagnostic systems, resulting in inaccurate diagnoses and assessments. These attacks exploit vulnerabilities in image processing, leading to misclassification or altered visual features that often go unnoticed. This raises serious concerns about the security and reliability of medical diagnosis, directly impacting clinical decision-making and patient safety. This research … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,742 accessesView PDFCite
Research ArticleOpen accessIn the abstractPreventing Deforestation in the Indian Landscape Through Neural Network-Based Intelligence Using Sound Event Detection and Advanced Feature Extraction TechniquesSallauddin Mohmmad, Suresh Kumar SanampudiForests play a vital role in maintaining ecological balance, regulating the climate, and conserving biodiversity. However, India’s forest landscape has witnessed significant changes between 1980 and 2024 due to deforestation, afforestation, and evolving conservation strategies. To address the challenges associated with forest monitoring, we proposed a model based on Sound Event Detection using a dataset comprising four classes: chainsaw sounds, … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractPoisson-Gamma Latent Dirichlet Allocation Model for Topics with Word DependenciesIbrahim Bakari Bala, Mohd Zainuri SaringatThis paper introduces the Poisson-Gamma Latent Dirichlet Allocation (PGLDA) model for modeling word dependencies in topics modeling. The Poisson document length distribution has been used extensively in the past for modeling topics with the expectation that its effect will fizzle out at the end of the model definition. This procedure often leads to downplaying the effect of word correlation with … …Journal of Computer Science, Vol. 16, Issue 12 · 3 Dec 2020 · 6,875 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning-Based Spectrum Sensing in Cognitive Radio Networks using Stacked LSTM: Performance Analysis of SNR and BERKavitha Veerappan, Seetharaman GopalakrishnanRapid evolution of wireless communication technologies and emergence of 5G networks have addressed lack of spectrum resources, highlighting the need for innovative topologies to improve the spectrum utilization. Due to this reason, Cognitive Radio (CR) has evolved as an optimized solution to overcome these difficulties by allowing dynamic spectrum access, thereby reducing the under-usage of available spectrum. Considering this, precise … …Journal of Computer Science, Vol. 21, Issue 11 · 19 Dec 2025 · 2,219 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Fleet Management with GPS Data in Port Terminals: A Deep Learning Architecture for Truck Position PredictionMohammed El Karkraoui, Hicham AttariuasEffective truck fleet management in port terminals is crucial for improving operational efficiency and reducing delays. However, GPS-based positioning systems often face limitations in port environments due to signal obstructions and network issues. This study explores the utilization of advanced methods for deep learning, particularly Recurrent Neural Networks (RNNs) for predicting truck positions when GPS signals are unavailable or unreliable. … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,271 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing 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 accessIn the abstractAnalyzing Temperature-Dependent Thermal Properties of Biomaterials Using Machine Learning MethodsArmaghan Shalbaftabar, Kristen Rhinehardt, Dhananjay KumarThis research utilizes machine learning models ANN, Random Forest, and Decision Tree to predict material properties of Ti-based biomaterials, including Young’s modulus, density, thermal conductivity, and specific heat at various temperatures. Data was sourced using web scraping and Plot Digitizer, validated against literature, and analyzed in Excel. The ANN model achieved strong performance, with R² = 0.980874 for TiAl and … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 12 Sep 2025 · 4,634 accessesView PDFCite
Review ArticleOpen accessIn the abstractWeb Scraping for Product Recommendations: A Review of Techniques and ApplicationsAmarinder Kaur, Deepak PrasharA comprehensive method for developing a reliable product recommender system leveraging sophisticated web scraping technologies, machine learning, and natural language processing techniques. The proposed system addresses key challenges in personalized product recommendation, including the difficulty of integrating diverse data from multiple e-commerce platforms, ensuring data quality, and improving recommendation accuracy to enhance user experience. Specifically, this research tackles issues related … …Journal of Computer Science, Vol. 21, Issue 6 · 21 Jun 2025 · 4,225 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultimedia Image Retrieval Using Novel Modelling of Combined Binary Patterns with Reduced DimensionsM. Geetha Yadav, SP. ChokkalingamAdvancements in computer vision have transformed image retrieval. However, many existing systems struggle to bridge the semantic gap between low-level features and high-level user expectations. This study proposed a new approach that combines texture and colour features to enhance retrieval accuracy and user satisfaction. The proposed method employs the HSV colour model to extract colour features, focusing on dominant features … …Journal of Computer Science, Vol. 21, Issue 4 · 14 Apr 2025 · 5,213 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel River Meander Migration and Cutoff Model: A New PerspectiveYoussef Ismail HafezAccurate prediction of river meander migration is crucial for effective river management and operation, particularly in light of climate changes and human-induced interventions. Existing models often rely on single-equation approaches, such as bank erosion rate versus excess bank velocity or excess bank shear stress, which limit their ability to comprehensively capture the complex dynamics of meander evolution. This study presents … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 21 Mar 2025 · 7,683 accessesView PDFCite