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28 results for “Attention Capture”
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Research ArticleOpen accessIn the keywordsEffects of Competing Lexical Distracters in a Visual Search TaskJeremy W. Grabbe, Tom Cioffi, Luke T. Zauner et al.Studies have shown that distracters that are relevant to a target can negatively affect visual search performance. Recent studies have looked at performance when targets are embedded within a distracter. Various factors have been explored such as automaticity, spatial location and timing. This study asked, &#34If distracters affected a different dimension would that produce a detriment to visual search performance&#34? … …Current Research in Psychology, Vol. 4, Issue 2 · 16 Jan 2014 · 7,373 accessesView PDFCite
Research ArticleOpen accessIn the abstractDual-Branch Shape Texture Learning With Pyramid Residual and Sobel Edge Layers for Rice Variety ClassificationM Pradeep, M SiddappaAutomated rice variety classification categorizes rice types based on features, such as grain texture, shape, color, and size. Traditional handcrafted feature-based models fail at rice classification due to lighting variations, background noise, and environmental conditions, leading to overlapping visual characteristics and frequent misclassification. To address these challenges, this research proposes a novel Dual-Branch Convolutional Neural Network with Pyramid Residual Units … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 627 accessesView PDFCite
Research ArticleOpen accessIn the abstractExplainable MedAttn-ResNet50 for Automated Kidney Tumor Classification from CT Images With Grad-CAM VisualizationD. Vetrithangam, Pramod Kumar, Shilpasree S. et al.Kidney tumor classification from CT imaging remains challenging due to CT-specific intensity variations, tumor heterogeneity, and limited clinically meaningful interpretability in existing deep learning models. To address these limitations, we propose an Explainable MedAttn-ResNet50 framework that integrates radiology-driven preprocessing, multi-scale feature extraction, and medical attention mechanisms within a unified architecture. The preprocessing pipeline applies radiology-inspired intensity normalization, contrast enhancement, and … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,120 accessesView PDFCite
Research ArticleOpen accessIn the abstractEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 912 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Deep Learning Model for Evaluating Subjective Answers Based on Semantic Textual SimilaritySiddhesh Kudtarkar, Kavita ShirsatSubjective answer evaluation requires accurately identifying semantic similarities between student and reference responses. This study introduces a Hybrid Deep Learning Model (HDLM) that integrates CNN, GRU, and LSTM architectures to assess Semantic Textual Similarity (STS) more effectively. The HDLM employs two parallel branches-CNN-GRU and CNN-LSTM to capture both local syntactic features and long-range contextual dependencies, followed by Manhattan distance for … …Journal of Computer Science, Vol. 22, Issue 4 · 7 Apr 2026 · 1,690 accessesView PDFCite
Research ArticleOpen accessIn the abstractHindi Poetry Translation Using Neural Machine TranslationPragya Tewari, Anurag Singh BaghelNeural Machine Translation (NMT) has become an essential tool in Natural Language Processing (NLP), enabling the automatic translation of text across languages. However, translating poetry remains a relatively unexplored and complex task. Unlike general text, poetry carries multiple layers of meaning, emotion, rhythm, and cultural nuance, making it difficult to capture in another language through standard translation techniques. This study … …Journal of Computer Science, Vol. 22, Issue 1 · 16 Feb 2026 · 1,773 accessesView PDFCite
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 abstractKSWN (Kannada SentiWordNet): Developing a Sentiment Lexicon for Kannada using Translation and Word Embedding TechniquesRashmi Kariganuru Bheemarao, Hassan Sadashiva Guruprasad, Shambhavi Bangalore RaviOpinion Mining has gained significant attention in recent years, especially due to the enormous growth of online content generation. However, finding the opinions expressed in comments and reviews is highly challenging in Indian regional languages due to the lack of annotated datasets. Opinion mining has predominantly been conducted in English, with recent efforts extending to Hindi and other languages. A … …Journal of Computer Science, Vol. 21, Issue 6 · 4 Jul 2025 · 3,377 accessesView PDFCite
Research ArticleOpen accessIn the abstractSM-SCAM YOLO: Enhancing Object Detection with Multi-Scale Module and Spatial Channel Attention MechanismShanmuga Sundari Mariyappan, Kayalvizhi Mohan, K. B. K. S. DurgaDetecting tiny objects remains a significant hurdle in computer vision, primarily due to scale variation, occlusion, and the loss of detail in low-resolution features. Although YOLO-based detectors are popular for their speed and efficiency in real-time tasks, they often struggle with accurately identifying small objects because of information loss during downsampling. This study introduces an improved YOLO-based model that integrates … …Journal of Computer Science, Vol. 21, Issue 6 · 12 Jun 2025 · 3,921 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification Model of Traditional Chinese Medicine Prescription Decocting Duration Combining Text Convolutional Neural Network with Attention MechanismZhibiao Li et al.The decocting time of Traditional Chinese Medicine (TCM) formulas is crucial for therapeutic effects. To better capture the important characteristics related to the decocting time of TCM formulas, a formula decocting time classification model TextCNN-attention that integrates the attention mechanism and Text Convolutional Neural Network is proposed. This model predicts the decocting time of formulas and divides them into long-term, … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 4 · 26 Sep 2024 · 4,366 accessesView PDFCite