Dhanesh Ramachandram

1.6k total citations · 1 hit paper
39 papers, 992 citations indexed

About

Dhanesh Ramachandram is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Dhanesh Ramachandram has authored 39 papers receiving a total of 992 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 16 papers in Artificial Intelligence and 6 papers in Aerospace Engineering. Recurrent topics in Dhanesh Ramachandram's work include Advanced Image and Video Retrieval Techniques (9 papers), Image Retrieval and Classification Techniques (8 papers) and Medical Image Segmentation Techniques (7 papers). Dhanesh Ramachandram is often cited by papers focused on Advanced Image and Video Retrieval Techniques (9 papers), Image Retrieval and Classification Techniques (8 papers) and Medical Image Segmentation Techniques (7 papers). Dhanesh Ramachandram collaborates with scholars based in Malaysia, Canada and United States. Dhanesh Ramachandram's co-authors include Graham W. Taylor, Rajeswari Mandava, Mohd Ezane Aziz, Osama Moh’d Alia, Ibrahim Lutfi Shuaib, Kok Haur Ong, José L. Ramírez-GarcíaLuna, Robert D. Fraser, Mozaherul Hoque Abul Hasanat and Alfian Abdul Halin and has published in prestigious journals such as IEEE Signal Processing Magazine, Neurocomputing and Neural Computing and Applications.

In The Last Decade

Dhanesh Ramachandram

38 papers receiving 965 citations

Hit Papers

Deep Multimodal Learning: A Survey on Recent Advances and... 2017 2026 2020 2023 2017 200 400 600
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.

  1. Deep Multimodal Learning: A Survey on Recent Advances and Trends
    2017 647 citations Dhanesh Ramachandram, Graham W. Taylor profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dhanesh Ramachandram Malaysia 13 397 345 145 90 73 39 992
Stefan Westberg United States 3 334 0.8× 282 0.8× 130 0.9× 79 0.9× 81 1.1× 6 1.2k
Brian C. Van Essen United States 6 340 0.9× 283 0.8× 132 0.9× 79 0.9× 82 1.1× 10 1.2k
Sansanee Auephanwiriyakul Thailand 16 445 1.1× 351 1.0× 132 0.9× 81 0.9× 99 1.4× 103 1.1k
Samina Khalid Pakistan 11 390 1.0× 236 0.7× 202 1.4× 89 1.0× 66 0.9× 27 1.1k
Chirag Patel India 11 255 0.6× 370 1.1× 120 0.8× 63 0.7× 74 1.0× 37 961
V́ıctor González-Castro Spain 20 311 0.8× 245 0.7× 138 1.0× 106 1.2× 102 1.4× 59 1.2k
Guitao Cao China 16 252 0.6× 345 1.0× 166 1.1× 52 0.6× 88 1.2× 84 924
Qianwei Zhou China 17 385 1.0× 294 0.9× 264 1.8× 78 0.9× 122 1.7× 62 1.1k
Tehmina Khalil Pakistan 9 372 0.9× 425 1.2× 268 1.8× 89 1.0× 79 1.1× 13 1.2k
Qinghe Zheng China 17 423 1.1× 477 1.4× 137 0.9× 146 1.6× 84 1.2× 39 1.3k

Countries citing papers authored by Dhanesh Ramachandram

Since Specialization
Citations

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

Fields of papers citing papers by Dhanesh Ramachandram

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dhanesh Ramachandram. 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 Dhanesh Ramachandram. The network helps show where Dhanesh Ramachandram may publish in the future.

Co-authorship network of co-authors of Dhanesh Ramachandram

This figure shows the co-authorship network connecting the top 25 collaborators of Dhanesh Ramachandram. A scholar is included among the top collaborators of Dhanesh Ramachandram 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 Dhanesh Ramachandram. Dhanesh Ramachandram 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.
Ramachandram, Dhanesh, et al.. (2023). Towards an AI-Based Objective Prognostic Model for Quantifying Wound Healing. IEEE Journal of Biomedical and Health Informatics. 28(2). 666–677. 12 indexed citations
2.
Ramachandram, Dhanesh, et al.. (2022). Fully Automated Wound Tissue Segmentation Using Deep Learning on Mobile Devices: Cohort Study. JMIR mhealth and uhealth. 10(4). e36977–e36977. 35 indexed citations
3.
Ramachandram, Dhanesh, et al.. (2018). Bayesian optimization on graph-structured search spaces: Optimizing deep multimodal fusion architectures. Neurocomputing. 298. 80–89. 18 indexed citations
4.
Ghani, Ahmad Shahrizan Abdul, et al.. (2017). Enhancement of Under-Exposed Image for Object Tracking Algorithm Through Homomorphic Filtering and Mean Histogram Matching. Advanced Science Letters. 23(11). 11257–11261. 7 indexed citations
5.
Ramachandram, Dhanesh & Graham W. Taylor. (2017). Skin Lesion Segmentation using Deep Hypercolumn Descriptors. 3(1). 8 indexed citations
6.
Ong, Kok Haur, Dhanesh Ramachandram, Rajeswari Mandava, & Ibrahim Lutfi Shuaib. (2012). Automatic white matter lesion segmentation using an adaptive outlier detection method. Magnetic Resonance Imaging. 30(6). 807–823. 36 indexed citations
7.
Hasanat, Mozaherul Hoque Abul, Dhanesh Ramachandram, & Rajeswari Mandava. (2010). Bayesian belief network learning algorithms for modeling contextual relationships in natural imagery: a comparative study. Artificial Intelligence Review. 34(4). 291–308. 14 indexed citations
8.
Mandava, Rajeswari, et al.. (2010). Osteosarcoma segmentation in MRI using dynamic Harmony Search based clustering. 423–429. 20 indexed citations
9.
Ramachandram, Dhanesh, et al.. (2010). Wavelet energy-guided level set-based active contour: A segmentation method to segment highly similar regions. Computers in Biology and Medicine. 40(7). 608–620. 12 indexed citations
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11.
Hasanat, Mozaherul Hoque Abul, et al.. (2009). ConVeS. 78–83. 1 indexed citations
12.
Ramachandram, Dhanesh, et al.. (2009). Optimizing Kernel Functions Using Transfer Learning from Unlabeled Data. 5. 111–117. 4 indexed citations
13.
Alia, Osama Moh’d, Rajeswari Mandava, Dhanesh Ramachandram, & Mohd Ezane Aziz. (2009). Harmony search-based cluster initialization for fuzzy c-means segmentation of MR images. 1–6. 23 indexed citations
14.
Ramachandram, Dhanesh, et al.. (2009). Multi-feature Based Object Class Recognition. 2. 324–329. 2 indexed citations
15.
Ramachandram, Dhanesh, et al.. (2009). A web-based framework for resource sharing and collaborative medical image annotation. 514–519. 1 indexed citations
16.
Ramachandram, Dhanesh, et al.. (2009). A Web-Based Framework for Distributed Medical Image Processing Using Image Markup Language (IML). 12. 470–475. 3 indexed citations
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18.
Ramachandram, Dhanesh, et al.. (2008). Object Based Clustering Using Hybrid Algorithms. 12–17. 1 indexed citations
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20.
Ramachandram, Dhanesh, et al.. (2004). Neural network-based robot visual positioning for intelligent assembly. Journal of Intelligent Manufacturing. 15(2). 219–231. 12 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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