Mia Rizkinia

Mia Rizkinia
University of Indonesia | UI · Department of Electrical Engineering

MT

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27
Publications
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160
Citations
Introduction
Mia Rizkinia currently works at the Department of Electrical Engineering, University of Indonesia. Mia does research in Computer Engineering. Their most recent publication is 'Joint Local Abundance Sparse Unmixing for Hyperspectral Images'.
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Publications

Publications (27)
Article
Full-text available
Forest and land fires are disasters that greatly impact various sectors. Burned area identification is needed to control forest and land fires. Remote sensing is used as common technology for rapid burned area identification. However, there are not many studies related to the combination of optical and synthetic aperture radar (SAR) remote sensing...
Article
Full-text available
Flooding in urban areas is counted as a significant disaster that must be correctly mitigated due to the huge amount of affected people, material losses, hampered economic activity, and flood-related diseases. One of the technologies available for disaster mitigation and prevention is satellites providing image data on previously flooded areas. In...
Conference Paper
Beta thalassemia is a type of hemoglobinopathy with a mutation occurring in the beta-globin gene (HBB), mainly identified by a low hemoglobin level in the body. Beta thalassemia (BT) patients undergo blood transfusion regularly due to their ineffective erythropoiesis mechanism. This condition leads to iron overload that results in further complicat...
Article
Full-text available
Cancer is one of the leading causes of death, and the brain is one of the body’s cancer-prone organs. The early detection of brain tumors can reduce cancer risk, which is practically assisted and conducted using scanners such as computed tomography (CT) and magnetic resonance imaging (MRI). However, those modalities are high-cost and large-sized, a...
Article
Full-text available
Anomaly detection is one of the most challenging topics in hyperspectral imaging due to the high spectral resolution of the images and the lack of spatial and spectral information about the anomaly. In this paper, a novel hyperspectral anomaly detection method called morphological profile and attribute filter (MPAF) algorithm is proposed. Aiming to...
Article
Full-text available
Hyperspectral anomaly detection aims at identifying unique objects with different spatial and spectral appearances from its surrounding pixels. One of the widely used conventional methods is Collaborative-Representation-Based Detector (CRD). CRD approximates each pixel on the background that can be represented by neighboring pixels, while the anoma...
Article
Full-text available
Magnetic resonance imaging (MRI) is an essential medical imaging technique which is widely used for medical research and diagnosis. Dynamic MRI provides the observed object visualization through time and results in a spatiotemporal signal. The image sequences often contain redundant information in both spatial and temporal domains. To utilize this...
Conference Paper
Full-text available
Credit as a part of our consumptive life has helped a lot of people. As a financial product, it is used widely along with the growth of economic and financial services. Therefore, credit is very risky so that motivating the financial institution to use a system called credit scoring to make a decision about acceptance. However, the conventional cre...
Article
Full-text available
Sparse unmixing is widely used for hyperspectral imagery to estimate the optimal fraction (abundance) of materials contained in mixed pixels (endmembers) of a hyperspectral scene, by considering the abundance sparsity. This abundance has a unique property, i.e., high spatial correlation in local regions. This is due to the fact that the endmembers...
Conference Paper
Hyperspectral sparse unmixing is a task to estimate the optimal fraction (abundance) of materials contained in mixed pixels (endmembers) of a hyperspectral scene, by considering the abundance sparsity. The abundance has a unique property, i.e., high spatial correlation in local regions. This is due to the fact that the endmembers existing in the re...
Article
We propose a method for local spectral component decomposition based on the line feature of local distribution. Our aim is to reduce noise on multi-channel images by exploiting the linear correlation in the spectral domain of a local region. We first calculate a linear feature over the spectral components of an M-channel image, which we call the sp...
Article
Using a flash/no-flash image pair, we propose a novel white-balancing technique that can effectively correct the color balance of a complex scene under multiple light sources. In the proposed method, by using multiple images of the same scene taken under different lighting conditions, we estimate the reflectance component of the scene and the multi...
Conference Paper
Full-text available
The geographical position of Indonesia located between two continents and oceans is strategic, but at large risk of experiencing various disasters. Climate change and vulnerable location (surrounded by plates and geological faults in the Earth's crust) creates an earthquake-prone region and causes land/mudslides. In this paper, PS InSAR method (Per...
Article
Full-text available
This study focuses on disaster observations in Pariaman (West Sumatera) and Wasior (Papua) using remote sensing techniques (differential SAR interferometry). Differential interferometry (DInSAR) method was performed on two PALSAR data sets with different acquisition months, i.e. about a month after and before disaster, respectively. The center dama...
Article
Full-text available
Flood that occurred in Jakarta is not only influenced by rainfall, urban planning system and drainage alone, but also may be involved land subsidence (LS). LS is possible in because Jakarta stands on top of layers of sediments and the presence of ground water consumption in very large quantities. In this research, the Advanced Land Observing Satell...

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