Výsledky vyhledávání - "K. Jayapriya"

Person re-identification using prioritized chromatic texture (PCT) with deep learning

Autor: K. Jayapriya, N. Ani Brown Mary, I. Jeena Jacob

Publikováno v: Multimedia Tools and Applications. 79:29399-29410

Person re-identification (re-ID) helps to identify a person’s attention in different cameras. But this is not an easy task, due to distance, illumination and lack of dataset. Nowadays, this field attracts many researchers because of its varied appl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::48f7c9d778658413079fe2f9bafdccc6
https://doi.org/10.1007/s11042-020-09528-8

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Hyperspectral image classification using multi-task feature leverage with multi-variant deep learning

Autor: Israel Jeena Jacob, K. Jayapriya, Paulraj Ebby Darney

Publikováno v: Earth Science Informatics. 13:1093-1102

Deep learning framework aids the researchers in learning different application areas to a greater extent. Deep learning framework is preferred over machine learning since it helps to learn the input from end to end, whereas latter one require the inp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1d662c0b03c87f90a424ea4193dc7c89
https://doi.org/10.1007/s12145-020-00485-2

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Hybrid fully convolutional networks‐based skin lesion segmentation and melanoma detection using deep feature

Autor: K. Jayapriya, Israel Jeena Jacob

Publikováno v: International Journal of Imaging Systems and Technology. 30:348-357

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d7d1c3264eb296d6fb6d1213d23266de
https://doi.org/10.1002/ima.22377

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Deep learned Inter-Channel Colored Texture Pattern: a new chromatic-texture descriptor

Autor: P. Ebby Darney, K. G. Srinivasagan, K. Jayapriya, I. Jeena Jacob

Publikováno v: Pattern Analysis and Applications. 23:239-251

Texture is a dominant tool for feature extraction. Incorporation of inter-channel chromatic information along with the texture feature will improve the accuracy of feature extraction. This paper provides deep learned Inter-Channel Colored Texture Pat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d37ea0787129d87a502356a1a90394c9
https://doi.org/10.1007/s10044-019-00780-9

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Volume-based inter difference XOR pattern: a new pattern for pulmonary nodule detection in CT images

Autor: K. Jayapriya, A. Chitradevi, N. Nirmal Singh

Publikováno v: International Journal of Biomedical Engineering and Technology. 36:172

The pulmonary nodule identification which paves the path to the cancer diagnosis is a challenging task today. The proposed work, volume-based inter difference XOR pattern (VIDXP) provides an efficient lung nodule detection system using a 3D texture-b

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7077c1b8f3ca101cdfd465cde848d5b2
https://doi.org/10.1504/ijbet.2021.10039245

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Employing a novel 2-gram subgroup intra pattern (2GSIP) with stacked auto encoder for membrane protein classification

Autor: N. Ani Brown Mary, K. Jayapriya

Publikováno v: Molecular biology reports. 46(2)

Cell membrane proteins play an essentially significant function in manipulating the behaviour of cells. Examination of amino acid sequences can put forward useful insights into the tertiary structures of proteins and their biological functions. One o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36cfd8f8a484d68308a3b0aadfa5b423
https://pubmed.ncbi.nlm.nih.gov/30778923

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Local Oppugnant Color Texture Pattern for image retrieval system

Autor: K. G. Srinivasagan, I. Jeena Jacob, K. Jayapriya

Publikováno v: Pattern Recognition Letters. 42:72-78

The current scenario of image retrieval pays attention to local texture patterns. The recently proposed Local Tetra Pattern (LTrP) represents the image by the directional information and gives promising results. This paper proposes Local Oppugnant Co

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e4870e0e15ed57b4e370696deec8eb9f
https://doi.org/10.1016/j.patrec.2014.01.017

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