Ramesh Kumar Lama

581 total citations
22 papers, 391 citations indexed

About

Ramesh Kumar Lama is a scholar working on Computer Vision and Pattern Recognition, Neurology and Cognitive Neuroscience. According to data from OpenAlex, Ramesh Kumar Lama has authored 22 papers receiving a total of 391 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 8 papers in Neurology and 5 papers in Cognitive Neuroscience. Recurrent topics in Ramesh Kumar Lama's work include Image and Signal Denoising Methods (7 papers), Brain Tumor Detection and Classification (7 papers) and Advanced Image Processing Techniques (6 papers). Ramesh Kumar Lama is often cited by papers focused on Image and Signal Denoising Methods (7 papers), Brain Tumor Detection and Classification (7 papers) and Advanced Image Processing Techniques (6 papers). Ramesh Kumar Lama collaborates with scholars based in South Korea and United States. Ramesh Kumar Lama's co-authors include Goo‐Rak Kwon, Yubraj Gupta, Sang‐Woong Lee, Jeong-Seon Park, Jeonghwan Gwak, Kyu Yeong Choi, Kun Ho Lee, Jang Jae Lee, Jae-Young Pyun and Sang-Woong Lee and has published in prestigious journals such as Sensors, Frontiers in Neuroscience and Applied Sciences.

In The Last Decade

Ramesh Kumar Lama

21 papers receiving 380 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ramesh Kumar Lama South Korea 10 140 111 105 89 83 22 391
L. Khedher Spain 7 123 0.9× 79 0.7× 90 0.9× 79 0.9× 72 0.9× 9 426
Diego Castillo-Barnés Spain 12 152 1.1× 95 0.9× 65 0.6× 139 1.6× 96 1.2× 25 462
Kanghan Oh South Korea 9 140 1.0× 100 0.9× 126 1.2× 157 1.8× 96 1.2× 19 461
Ashraf Haroon Rashid India 7 237 1.7× 97 0.9× 127 1.2× 206 2.3× 73 0.9× 8 532
Siqi Liu China 5 160 1.1× 102 0.9× 93 0.9× 154 1.7× 103 1.2× 12 507
ADNI ADNI United States 7 257 1.8× 180 1.6× 133 1.3× 179 2.0× 94 1.1× 11 501
Yubraj Gupta Germany 8 125 0.9× 135 1.2× 41 0.4× 82 0.9× 70 0.8× 19 312
S Spasov Italy 5 136 1.0× 146 1.3× 52 0.5× 131 1.5× 68 0.8× 9 359
Won-Mo Jung South Korea 13 90 0.6× 95 0.9× 106 1.0× 111 1.2× 83 1.0× 38 624
Rahul Sharma India 10 198 1.4× 67 0.6× 108 1.0× 139 1.6× 50 0.6× 17 419

Countries citing papers authored by Ramesh Kumar Lama

Since Specialization
Citations

This map shows the geographic impact of Ramesh Kumar Lama'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 Ramesh Kumar Lama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ramesh Kumar Lama more than expected).

Fields of papers citing papers by Ramesh Kumar Lama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ramesh Kumar Lama. 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 Ramesh Kumar Lama. The network helps show where Ramesh Kumar Lama may publish in the future.

Co-authorship network of co-authors of Ramesh Kumar Lama

This figure shows the co-authorship network connecting the top 25 collaborators of Ramesh Kumar Lama. A scholar is included among the top collaborators of Ramesh Kumar Lama 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 Ramesh Kumar Lama. Ramesh Kumar Lama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lama, Ramesh Kumar, et al.. (2024). Design and Performance Analysis of Foldable Solar Panel for Agrivoltaics System. Sensors. 24(4). 1167–1167. 8 indexed citations
2.
Lama, Ramesh Kumar & Goo‐Rak Kwon. (2023). Resting-State Functional Connectivity Difference in Alzheimer’s Disease and Mild Cognitive Impairment Using Threshold-Free Cluster Enhancement. Diagnostics. 13(19). 3074–3074. 1 indexed citations
3.
Lama, Ramesh Kumar, Ji‐In Kim, & Goo‐Rak Kwon. (2022). Classification of Alzheimer’s Disease Based on Core-Large Scale Brain Network Using Multilayer Extreme Learning Machine. Mathematics. 10(12). 1967–1967. 10 indexed citations
4.
Lama, Ramesh Kumar & Goo‐Rak Kwon. (2021). Diagnosis of Alzheimer’s Disease Using Brain Network. Frontiers in Neuroscience. 15. 605115–605115. 25 indexed citations
5.
Lama, Ramesh Kumar, et al.. (2021). Diagnosis of Alzheimer's disease using Effective Connectivity of rs-fMRI. 1–4. 2 indexed citations
6.
Gupta, Yubraj, Ramesh Kumar Lama, Sang‐Woong Lee, & Goo‐Rak Kwon. (2020). An MRI brain disease classification system using PDFB-CT and GLCM with kernel-SVM for medical decision support. Multimedia Tools and Applications. 79(43-44). 32195–32224. 10 indexed citations
7.
Lee, Kun Ho, Kyu Yeong Choi, Jang Jae Lee, et al.. (2020). Classification of Alzheimer’s Disease and Mild Cognitive Impairment Based on Cortical and Subcortical Features from MRI T1 Brain Images Utilizing Four Different Types of Datasets. Journal of Healthcare Engineering. 2020. 1–14. 31 indexed citations
8.
Lama, Ramesh Kumar & Sang-Woong Lee. (2020). White Matter Network Alterations in Alzheimer’s Disease Patients. Applied Sciences. 10(3). 919–919. 6 indexed citations
9.
10.
Kwon, Goo‐Rak, et al.. (2019). Comparative analysis of Alzheimer's disease classification by CDR level using CNN, feature selection, and machine‐learning techniques. International Journal of Imaging Systems and Technology. 29(3). 297–310. 47 indexed citations
11.
Ko, Sung-Jea, et al.. (2018). Color image interpolation in the DCT domain using a wavelet-based differential value. Multimedia Tools and Applications. 77(16). 21539–21556. 4 indexed citations
12.
Lama, Ramesh Kumar, Jeonghwan Gwak, Jeong-Seon Park, & Sang‐Woong Lee. (2017). Diagnosis of Alzheimer’s Disease Based on Structural MRI Images Using a Regularized Extreme Learning Machine and PCA Features. Journal of Healthcare Engineering. 2017. 1–11. 88 indexed citations
13.
Lama, Ramesh Kumar, et al.. (2016). Interpolation using wavelet transform and discrete cosine transform for high resolution display. 184–186. 7 indexed citations
14.
Lama, Ramesh Kumar, et al.. (2016). Image interpolation for high-resolution display based on the complex dual-tree wavelet transform and hidden Markov model. Multimedia Tools and Applications. 75(23). 16487–16498. 9 indexed citations
15.
Lama, Ramesh Kumar & Goo‐Rak Kwon. (2015). Detection of Alzheimer Disease Using Grow Cut Method and Brain Volume Estimation. The Journal of Korean Institute of Information Technology. 13(4). 139–139.
16.
Lama, Ramesh Kumar & Goo‐Rak Kwon. (2015). New interpolation method based on combination of Discrete cosine transform and wavelet transform. 10. 363–366. 2 indexed citations
17.
Kwon, Goo‐Rak, Ramesh Kumar Lama, Jae-Young Pyun, & Chun‐Su Park. (2015). Multimedia digital rights management based on selective encryption for flexible business model. Multimedia Tools and Applications. 75(12). 6697–6715. 4 indexed citations
18.
19.
Lama, Ramesh Kumar & Goo‐Rak Kwon. (2013). Multiple Description Coding Using Directional Discrete Cosine Transform. Journal of information and communication convergence engineering. 11(4). 293–297. 3 indexed citations
20.
Lama, Ramesh Kumar, et al.. (2013). SVD based improved secret fragment visible mosaic image generation for information hiding. Multimedia Tools and Applications. 73(2). 873–886. 10 indexed citations

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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