Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Rika Sustika"'
Publikováno v:
IEEE Access, Vol 12, Pp 162285-162298 (2024)
In recent years, deep convolutional neural networks (CNNs) have significantly improved pansharpening performance compared to traditional methods. However, existing CNN-based methods for pansharpening still lack spatial detail and suffer from spectral
Externí odkaz:
https://doaj.org/article/26b8494162f246e6a02990e95ece1f92
Autor:
Rika Sustika
Publikováno v:
Computer Engineering and Applications Journal. 10:1-8
Remote sensing images generally have low spatial resolution because of the limitations of sensing devices, bandwidth transmission, or storage capacity. An effective way to improve spatial resolution with low cost is by using algorithm based approach,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9de3dc2603de1a34efa09a5283b946f
https://doi.org/10.18495/comengapp.v10i1.351
https://doi.org/10.18495/comengapp.v10i1.351
Publikováno v:
2020 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET).
Improving image resolution, especially spatial resolution, has been one of the most important concerns on remote sensing research communities. An efficient solution for improving spatial resolution is by using algorithm, known as super-resolution (SR
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2fdd608222d1151ca7dc3f8e40c4ad77
https://doi.org/10.1109/icramet51080.2020.9298648
https://doi.org/10.1109/icramet51080.2020.9298648
Publikováno v:
2018 International Conference on Computer, Control, Informatics and its Applications (IC3INA).
Developing an automatic detector of plant diseases is one of application fields in machine learning. Ground-truth diagnoses of plant diseases which are conducted by experts in laboratory tests are often inapplicable for fast and cheap implementations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7a13057e817d837bb1b1aad785e608e
https://doi.org/10.1109/ic3ina.2018.8629518
https://doi.org/10.1109/ic3ina.2018.8629518
Publikováno v:
2018 International Conference on Computer, Control, Informatics and its Applications (IC3INA).
This paper compares several image processing-based features for Support Vector Machine (SVM) to classify strawberries quality. We use binary class labels: good and damaged strawberries. We collect a new dataset taken from a webcam, consisting of 382
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::482993060325e1950d3c57b67674e554
https://doi.org/10.1109/ic3ina.2018.8629534
https://doi.org/10.1109/ic3ina.2018.8629534
Publikováno v:
2018 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET).
Cognitive radio is one of solution to increase the efficient usage of frequency by spectrum sharing. One important compenent in the spectrum sharing is spectrum management system. The spectrum management system distributes information of white space.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b52ae4ab2c858c6b14746f94d21c7e54
https://doi.org/10.1109/icramet.2018.8683930
https://doi.org/10.1109/icramet.2018.8683930
Publikováno v:
2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS).
Plant diseases outbreaks can cause significant threat to food security. Early detection of the diseases using machine learning could avoid such disaster. Currently, deep learning, which is a recent technology in machine learning, gained much populari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf5118125b55f2f953c98074b877628a
https://doi.org/10.1109/icacsis.2018.8618169
https://doi.org/10.1109/icacsis.2018.8618169
Publikováno v:
2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE).
Deep Learning technologies are becoming the major approaches for natural signal and information processings, including for speech recognition. Many architectures for deep learning have been proposed for automatic speech recognition (ASR). In this pap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a39fc43d6a698474ba7796ad75576ae
https://doi.org/10.1109/icitisee.2017.8285488
https://doi.org/10.1109/icitisee.2017.8285488
Publikováno v:
2017 International Conference on Computer, Control, Informatics and its Applications (IC3INA).
The problem of noise robustness remains one of main issues in automatic speech recognition (ASR) studies. The introduction of deep neural network (DNN) technologies, while significantly improves the ASR accuracies, still has not achieved a satisfacto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59549c652d2230d4d9cdfd77e67fde2c
https://doi.org/10.1109/ic3ina.2017.8251740
https://doi.org/10.1109/ic3ina.2017.8251740
Publikováno v:
2017 International Conference on Computer, Control, Informatics and its Applications (IC3INA).
The motif discovery problems such as DNA motifs need effective methods to search and process due to high computational loads. One of the problems needs to be solved is called Multi-Objective Optimization Problems (MOPS). To solve MOPS requires Evolut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::053e7a90bcac892387f2bb6dc7db0e0d
https://doi.org/10.1109/ic3ina.2017.8251741
https://doi.org/10.1109/ic3ina.2017.8251741