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110 results for “Computer Vision”
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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 · 7,228 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 · 6,044 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 · 7,326 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 · 7,003 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 · 7,956 accessesView PDFCite
Research ArticleOpen accessIn the abstractHarmonic Mean Projection Shape Transform for Leaf ClassificationSophia Jamila Zahra, Riza Sulaiman, Seyed M.M. Kahaki, Anton Satria PrabuwonoShape feature extraction has emerged as an important part of computer vision and image processing applications. Identification of shape objects in huge data based on shape similarity still remains a challenging problem due to the similarity of the shapes and existing of classes with similar contour information. This paper presents to investigate the shape analysis for plant leaf classification by … …Journal of Computer Science, Vol. 16, Issue 9 · 13 Sep 2020 · 6,854 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 · 8,125 accessesView PDFCite
Research ArticleOpen accessIn the abstractFUSION OF COLOR AND MODIFIED WEBER’S LAW DESCRIPTOR BASED HUMAN SKIN DETECTIONC. Prema, D. ManimegalaiSkin detection in images or videos plays a vital role in a wide range of image processing applications like face detection, face tracking, gesture analysis, human-computer interaction etc. Due to its high processing speed and invariant against rotation, it has received significant interest in pattern recognition and computer vision. The robustness of skin detection using color information depends on real … …Journal of Computer Science, Vol. 10, Issue 9 · 19 Apr 2014 · 6,397 accessesView PDFCite
Research ArticleOpen accessIn the abstractPALMPRINT VERIFICATION USING INVARIANT MOMENTS BASED ON WAVELET TRANSFORMInass SH. Hussein, Md Jan NordinData security is one of the important issues among computer users. Data security can prevent fraudulent users from accessing an individual's personal data. The biometrics recognition as one of the most important parts in the security of the data and the application of computer vision. The biometrics is the authentication method used in a wide variety of applications such as … …Journal of Computer Science, Vol. 10, Issue 8 · 7 Mar 2014 · 6,492 accessesView PDFCite