Novel Deep Learning Technique to Improve Resolution of Low-Quality Finger Print Image for Bigdata Applications

被引:0
|
作者
Lisha, P.P. [1 ]
Jayasree, V.K. [2 ]
机构
[1] Govt. Model Engineering College, Kerala, Ernakulam,682021, India
[2] Dept. of Electronics and Communication, Govt. Model Engineering College, Kerala, Ernakulam,682021, India
关键词
Convolution neural network - Finger print - Fingerprint images - High-resolution images - Image super resolutions - Learning techniques - Low resolution images - Lower resolution - Single image super-resolution - Single images;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:718 / 724
相关论文
共 50 条
  • [21] Robust and Lightweight Deep Learning Model for Industrial Fault Diagnosis in Low-Quality and Noisy Data
    Shin, Jaegwang
    Lee, Suan
    ELECTRONICS, 2023, 12 (02)
  • [22] Deep learning-based reconstruction can improve the image quality of low radiation dose head CT
    Yasunori Nagayama
    Koya Iwashita
    Natsuki Maruyama
    Hiroyuki Uetani
    Makoto Goto
    Daisuke Sakabe
    Takafumi Emoto
    Kengo Nakato
    Shinsuke Shigematsu
    Yuki Kato
    Sentaro Takada
    Masafumi Kidoh
    Seitaro Oda
    Takeshi Nakaura
    Masahiro Hatemura
    Mitsuharu Ueda
    Akitake Mukasa
    Toshinori Hirai
    European Radiology, 2023, 33 : 3253 - 3265
  • [23] Deep learning-based reconstruction can improve the image quality of low radiation dose head CT
    Nagayama, Yasunori
    Iwashita, Koya
    Maruyama, Natsuki
    Uetani, Hiroyuki
    Goto, Makoto
    Sakabe, Daisuke
    Emoto, Takafumi
    Nakato, Kengo
    Shigematsu, Shinsuke
    Kato, Yuki
    Takada, Sentaro
    Kidoh, Masafumi
    Oda, Seitaro
    Nakaura, Takeshi
    Hatemura, Masahiro
    Ueda, Mitsuharu
    Mukasa, Akitake
    Hirai, Toshinori
    EUROPEAN RADIOLOGY, 2023, 33 (05) : 3253 - 3265
  • [24] Improved image quality in abdominal computed tomography reconstructed with a novel Deep Learning Image Reconstruction technique - initial clinical experience
    Njolstad, Tormund
    Schulz, Anselm
    Godt, Johannes C.
    Brogger, Helga M.
    Johansen, Cathrine K.
    Andersen, Hilde K.
    Martinsen, Anne Catrine T.
    ACTA RADIOLOGICA OPEN, 2021, 10 (04)
  • [25] A Novel Technique for Image Captioning Based on Hierarchical Clustering and Deep Learning
    Rizwan Ur Rahman
    Pavan Kumar
    Aditya Mohan
    Rabia Musheer Aziz
    Deepak Singh Tomar
    SN Computer Science, 6 (4)
  • [26] Single Image Super-Resolution Technique using Precision learning of Low Resolution Images
    Salam, Amritha Abdul
    Mahadevappa, Manjunatha
    PROCEEDINGS OF THE 2019 IEEE REGION 10 CONFERENCE (TENCON 2019): TECHNOLOGY, KNOWLEDGE, AND SOCIETY, 2019, : 306 - 310
  • [27] Deep Learning for Reconstructing Low-Quality FTIR and Raman Spectra-A Case Study in Microplastic Analyses
    Brandt, Josef
    Mattsson, Karin
    Hassellov, Martin
    ANALYTICAL CHEMISTRY, 2021, 93 (49) : 16360 - 16368
  • [28] Comparison of deep learning systems and cornea specialists in detecting corneal diseases from low-quality images
    Li, Zhongwen
    Jiang, Jiewei
    Qiang, Wei
    Guo, Liufei
    Liu, Xiaotian
    Weng, Hongfei
    Wu, Shanjun
    Zheng, Qinxiang
    Chen, Wei
    ISCIENCE, 2021, 24 (11)
  • [29] Low-Quality Sensor Data-Based Semi-Supervised Learning for Medical Image Segmentation
    Li, Hengfan
    Xu, Xuanbo
    Liu, Ziheng
    Xia, Qingfeng
    Xia, Min
    SENSORS, 2024, 24 (23)
  • [30] Can deep learning improve image quality of low-dose CT: a prospective study in interstitial lung disease
    Ruijie Zhao
    Xin Sui
    Ruiyao Qin
    Huayang Du
    Lan Song
    Duxue Tian
    Jinhua Wang
    Xiaoping Lu
    Yun Wang
    Wei Song
    Zhengyu Jin
    European Radiology, 2022, 32 : 8140 - 8151