Malinda Vania

495 total citations · 1 hit paper
9 papers, 316 citations indexed

About

Malinda Vania is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Malinda Vania has authored 9 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Biomedical Engineering, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Malinda Vania's work include Medical Imaging and Analysis (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Medical Image Segmentation Techniques (2 papers). Malinda Vania is often cited by papers focused on Medical Imaging and Analysis (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Medical Image Segmentation Techniques (2 papers). Malinda Vania collaborates with scholars based in South Korea, United States and Indonesia. Malinda Vania's co-authors include Sunghoon Lim, Deukhee Lee, Bayu Adhi Tama, Seung‐Chul Lee, Sung‐Won Kim, Kihwan Choi, Hasan Maulahela and Sun‐Hee Kim and has published in prestigious journals such as IEEE Access, Artificial Intelligence Review and Journal of Computational Design and Engineering.

In The Last Decade

Malinda Vania

9 papers receiving 304 citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals

2022 147 citations Bayu Adhi Tama, Malinda Vania et al. Artificial Intelligence Review profile →

Peers

Countries citing papers authored by Malinda Vania

Since Specialization

Citations

This map shows the geographic impact of Malinda Vania's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Malinda Vania with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Malinda Vania more than expected).

Fields of papers citing papers by Malinda Vania

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Malinda Vania. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Malinda Vania. The network helps show where Malinda Vania may publish in the future.

Co-authorship network of co-authors of Malinda Vania

This figure shows the co-authorship network connecting the top 25 collaborators of Malinda Vania. A scholar is included among the top collaborators of Malinda Vania based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Malinda Vania. Malinda Vania is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

#	Work	Indexed citations
1	Recent Advances in Applying Machine Learning and Deep Learning to Detect Upper Gastrointestinal Tract Lesions 2023 ·IEEE Access ·Malinda Vania, Bayu Adhi Tama, Hasan Maulahela, Sunghoon Lim	13
2	An EfficientNet-Based Weighted Ensemble Model for Industrial Machine Malfunction Detection Using Acoustic Signals 2022 ·IEEE Access ·Bayu Adhi Tama, Malinda Vania, (unknown), Sunghoon Lim	17
3	Recent advances in the application of deep learning for fault diagnosis of rotating machinery using vibration signals breakdown → 2022 ·Artificial Intelligence Review ·Bayu Adhi Tama, Malinda Vania, Seung‐Chul Lee, Sunghoon Lim	147
4	Intervertebral disc instance segmentation using a multistage optimization mask-RCNN (MOM-RCNN) 2021 ·Journal of Computational Design and Engineering ·Malinda Vania, Deukhee Lee	25
5	Lumbar Vertebrae Synthetic Segmentation in Computed Tomography Images Using Hybrid Deep Generative Adversarial Networks 2020 ·PubMed ·Malinda Vania, Deukhee Lee	3
6	Three Dimensional Microrobot Tracking Using Learning-based System 2019 ·International Journal of Control Automation and Systems ·(unknown), (unknown), Malinda Vania, Deukhee Lee	12
7	Automatic spine segmentation from CT images using Convolutional Neural Network via redundant generation of class labels 2019 ·Journal of Computational Design and Engineering ·Malinda Vania, (unknown), Deukhee Lee	81
8	Semi-Supervised Learning for Low-Dose CT Image Restoration with Hierarchical Deep Generative Adversarial Network (HD-GAN) 2019 ·PubMed ·Kihwan Choi, Malinda Vania, Sung‐Won Kim	17
9	Automatic multisegmentation of abdominal organs by level set with weighted global and local forces 2016 ·Malinda Vania, Sun‐Hee Kim, Deukhee Lee	1

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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