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103 articles for “Computer vision”
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Review ArticleOpen accessIn the abstractFederated Learning for Analysis of Medical Images: A SurveyMuhammad Imran Sharif, Mehwish Mehmood, Md Palash Uddin et al.Machine learning models trained in medical imaging can help in the early detection, diagnosis, and prognosis of the disease. However, it confronts two major obstacles: deep learning models require access to a substantial amount of imaging data, which is a hard constraint, and the patient data is private and sensitive, so it cannot be shared like 1 other imaging data … …Journal of Computer Science, Vol. 20, Issue 12 · 28 Oct 2024 · 11,838 accessesView PDFCite
Research ArticleOpen accessIn the abstractPresentation of the New Invention of an Emergency System that Saves an Airplane after an Accident or Failure with a Navigation Application of the New Invention about Rotating ObjectsAkram LouizChandu, B., Pant, R., & Moudgalya, K. (2007). Modeling and Simulation of a Precision Navigation System using Pseudolites Mounted on Airships. 7th AIAA ATIO Conf, 2nd CEIAT Int’l Conf on Innov and Integr in Aero Sciences,17th LTA Systems Tech Conf; Followed by 2nd TEOS Forum, 7746. https://doi.org/10.2514/6.2007-7746 Giroux, A., Richter, T. G., & Moy, N. (2021). System and method for … …Journal of Aircraft and Spacecraft Technology, Vol. 8, Issue 1 · 25 May 2024 · 9,980 accessesView PDFCite
Research ArticleOpen accessIn the abstractRadiometric Invariant Dense Disparity Estimation for Real Time Stereo CorrespondenceDeepambika V. A., M. Abdul RahimanComputer stereo vision tries to mimic human vision by grabbing multiple views of the same scene and cognizing it. The stereo correspondence will find out the matching pixels between the two views based on the Lambertian criteria, which results in disparity. The distance of the objects from the camera can be calculated using this disparity. But in the real world … …Journal of Computer Science, Vol. 15, Issue 4 · 11 Apr 2019 · 7,232 accessesView PDFCite
Research ArticleOpen accessIn the abstractDataset of Selected Medicinal Plant Species of the Genus Brachylaena: A Comparative Application of Deep Learning Models for Plant Leaf RecognitionAvuya Deyi, Arnaud Nguembang Fadja, Eleonora Deborah Goosen et al.Since several active pharmaceutical ingredients are sourced from medicinal plants, identifying and classifying these plants are generally a valuable and essential task during the drug manufacturing process. For many years, identifying and classifying those plants have been exclusively done by experts in the domain, such as botanists and herbarium curators. Recently, powerful computer vision technologies, using deep learning or deep … …Journal of Computer Science, Vol. 19, Issue 11 · 17 Oct 2023 · 6,231 accessesView PDFCite
Research ArticleOpen accessIn the abstractRF-CNNS: Thin Deep Learning Networks For Accelerating Traffic Signs RecognitionBtissam Bousarhane, Driss BouzidiRoad scene analysis is a wide domain of research that aims to ameliorate the environmental perception in intelligent transportation systems, including autonomous vehicles and advanced driver-assistance systems. It also plays a crucial role in road safety improvement, by contributing to the reduction of traffic accidents' rate. Ensuring an efficient recognition of traffic signs contributes enormously to making cars safer, which … …Journal of Computer Science, Vol. 19, Issue 10 · 18 Sep 2023 · 5,338 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimised Implementation of Dense Stereo Correspondence for Resource Limited HardwareDeepambika Vadekkettathu Anirudhan, Malangai Abdul RahimanComputer stereo vision is a passive sensing technique that helps to recover 3D information of an environment from 2D images. The stereo correspondence is a challenging task that finds out matching pixels between the stereo image pair based on Lambertian criteria and its result is a disparity space image. The depth of the objects from the camera can be calculated … …Journal of Computer Science, Vol. 14, Issue 10 · 18 Oct 2018 · 7,332 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalyzing Effect on Residual Learning by Gradual Narrowing Fully-Connected Layer Width and Implementing Inception Block in Convolution LayerSaurabh SharmaResearch conducted on the advancement of CNN architecture for computer vision problems focuses on strategically choosing and modifying convolution hyperparameters (kernel, pooling, etc.). However, these research works don't exploit the advantage of employing multi fully-connected layers post the core schema to avail further performance improvements, which have been identified as the first research gap. Studies were also conducted to address … …Journal of Computer Science, Vol. 18, Issue 5 · 24 May 2022 · 6,051 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnsupervised Cosegmentation Model based on Saliency Detection and Optimized Hue Saturation Value Features of SuperpixelsRasha Shoitan, Mona M. MoussaSegmenting out the foreground from a single image remains a challenge in computer vision. Image co-segmentation has been used recently to alleviate the single image segmentation by exploiting the information of the common object to be segmented from a group of images having the same object. This research proposes an unsupervised co-segmentation technique based on saliency detection and optimized features … …Journal of Computer Science, Vol. 17, Issue 7 · 3 Aug 2021 · 7,009 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeafsnapNet: An Experimentally Evolved Deep Learning Model for Recognition of Plant Species based on Leafsnap Image DatasetEmmanuel Adetiba et al.Plants are very important living organisms on earth because humans and animals depend on them for nutrition, oxygen, medicine and balance in the ecosystem. Therefore, plant species recognition is critical to the improvement of agricultural productivity, mitigation of climate change and the discovery of new medicinal plants. However, species recognition has remained a difficult task even for trained botanists, because … …Journal of Computer Science, Vol. 17, Issue 3 · 1 Apr 2021 · 7,961 accessesView PDFCite
Research ArticleOpen accessIn the abstractIdentification of Human Emotions via Univariate and Multivarite Multiscale EntropyKawser AhammedThis work analyzes the emotions of human in terms of complexity. This analysis is achieved by applying both univariate and multivariate multiscale entropy methods on a multimodal dataset. Most of the contemporary human-computer interaction systems are unable to identify human affective states. So, the benefit of analyzing human emotions is to fill this gap by detecting human affective states. The … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 3 · 23 Jul 2015 · 8,128 accessesView PDFCite