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114 articles for “Robustness results”
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Research ArticleOpen accessIn the abstractGait Analysis Combining Sports Biomechanics and ImagingChao ZhuAiming at the problems of marker positioning error, soft tissue interference, and insufficient personalized modeling ability in traditional gait analysis, this study proposes a gait assessment method that integrates sports biomechanics and multimodal imaging analysis. Firstly, based on the public OU-ISIR gait database, a Convolutional Neural Network (CNN) is used to extract the key gait features in the human silhouette … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 20 Jul 2026 · 858 accessesView PDFCite
Research ArticleOpen accessIn the abstractUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractTime Series Analysis for Predicting Tea Harvest Yield: A SARIMAX-Based ApproachPallavi Nagpal, Deepika Chaudhary, Jaiteg SinghPrecise prediction of tea yield is crucial for both agricultural planning and economic forecasting. Projection of the future trends, which rely on present and historical data, is the process termed 'forecasting'. Yield prediction is fundamental for research and development. By gathering the yield data over historic times, the researchers can make their work more valuable by predicting the yield patterns. … …Journal of Computer Science, Vol. 22, Issue 2 · 19 Feb 2026 · 1,900 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnimal Health Prediction Using Hybrid KNN Based Vector Neighbor Classification Model: A Machine Learning ApproachJ. Rathi, A. SumathiAnimal condition disease prediction is a crucial task in veterinary medicine, and accurate prediction can significantly improve animal health and reduce economic losses. This paper proposed a novel hybrid classification model that combines an Improved Fuzzy-based feature selection process with a Hybrid KNN-based Vector Neighbor Classification model to enhance animal condition disease prediction. The proposed model aims to improve the … …Journal of Computer Science, Vol. 21, Issue 9 · 21 Oct 2025 · 2,905 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Feature Extraction Dual DCT-DWT Image Watermarking Combined with Chaos-Based CryptosystemKumari Rinki, Pushpneel Verma, Tanupriya Choudhury, Bhupesh Kumar SinghAs a result of the emerging technologies such as Internet-of-Things (IoT), data analysis and automation in many aspects of identity, watermarking has become increasingly important. A majority of prior systems focused on watermark embedding and recovery techniques for binary and grey-scale images in one specified region of the cover image, making the system less dependable. This study develops a novel … …Journal of Computer Science, Vol. 17, Issue 10 · 13 Nov 2021 · 6,098 accessesView PDFCite
Research ArticleOpen accessIn the abstractCompressive Sensing Theory for Improving the Robustness and the Security of the Discrete Wavelet Transform-Singular Value Decomposition Watermarking SchemeRasha Shoitan, Sawsan Morkos GharghoryDigital watermarking has been suggested as a solution to protect copyright and ownership of digital images. The effective watermarking scheme should satisfy imperceptibility, robustness, capacity and security requirements. In this research, the security issue and the lack of reconstruction quality of the watermark logo of the integration of Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD) and Compressive Sensing (CS) … …Journal of Computer Science, Vol. 17, Issue 4 · 28 Apr 2021 · 6,603 accessesView PDFCite
Research ArticleOpen accessIn the abstractModified U-Net With VGG11-BN Encoder and Frost Filter Based Pre-Processing for Copy Move Forgery LocalizationAshutosh Pandey, Niranjan Lal, Ashish Kumar ChakravertiCopy-move forgery is a widely used forgery method in digital image forensics, which involves copying and pasting a part of an image into another part of the image to hide or duplicate the visual information. This makes it difficult to detect such manipulations, particularly when the regions are subjected to geometric and photometric transformations. A Frost Filter-Enhanced Encoder-Decoder U-Net is … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 470 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermination of Crop Yield Detection and Prediction With Multimodal Data Using Fusion TechniquesKutlwano Sedimo, Rajalakshmi Selveraj, Venumadhav Kuthadi, Thulaganyo DimakatsoMost often, soil, environmental, and agronomic data are used in pieces, hence limiting the performance of crop selection and yield forecasting. This study develops an integrated, fusion-based framework that combines soil image classification, environmental feature analysis, and input-driven yield prediction to support precise agricultural decision-making. The system consists of three major modules: (i) a CNN for the classification of soil … …Journal of Computer Science, Vol. 22, Issue 10 · 5 Oct 2026 · 494 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Knowledge Driven Multi-Scale Spatiotemporal Fusion Framework for Reliable Multi-Horizon Traffic Flow ForecastingDeepika M S, P. Deepa Shenoy, Venugopal K RAccurate traffic flow forecasting remains a core challenge in intelligent transportation systems. Urban traffic patterns are characterised by complex spatiotemporal dependencies and inherent uncertainties, which complicate traffic forecasting. This study proposes a Dynamic Knowledge-Driven Spatiotemporal Fusion (DKDMSF) architecture to extract features of Multi-Scale traffic dynamics across various temporal traffic horizons. DKDMSF integrates Dynamic Spatial Attention (DSA) and Adaptive Graph Learning … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 422 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 · 1,127 accessesView PDFCite