A. Jayachandran

448 total citations
28 papers, 278 citations indexed

About

A. Jayachandran is a scholar working on Computer Vision and Pattern Recognition, Neurology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, A. Jayachandran has authored 28 papers receiving a total of 278 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 15 papers in Neurology and 11 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in A. Jayachandran's work include Brain Tumor Detection and Classification (15 papers), Retinal Imaging and Analysis (9 papers) and Digital Imaging for Blood Diseases (8 papers). A. Jayachandran is often cited by papers focused on Brain Tumor Detection and Classification (15 papers), Retinal Imaging and Analysis (9 papers) and Digital Imaging for Blood Diseases (8 papers). A. Jayachandran collaborates with scholars based in India and Pakistan. A. Jayachandran's co-authors include R. Dhanasekaran, Thinagaran Perumal, S. Kannadhasan and Alwin Poulose and has published in prestigious journals such as Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Neural Computing and Applications and Measurement.

In The Last Decade

A. Jayachandran

26 papers receiving 239 citations

Peers

A. Jayachandran

CVPR

NEURO

RNMI

OPHTH

Yepuganti Karuna India

Eman AbdelMaksoud Egypt

Xuanya Li China

Khin Yadanar Win Thailand

Milad Soltany Canada

Ayesha Jabbar China

Nagur Shareef Shaik India

Priyadarshini Adyasha Pattanaik India

Shahab Aslani United Kingdom

Giri Babu Kande India

Yepuganti Karuna India

A. Jayachandran

141 ×0.8

CVPR

110 ×0.7

NEURO

73 ×0.6

RNMI

60 ×0.9

23 ×0.4

OPHTH

Citations per year, relative to A. Jayachandran A. Jayachandran (= 1×) peers Yepuganti Karuna

Countries citing papers authored by A. Jayachandran

Since Specialization

Citations

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

Fields of papers citing papers by A. Jayachandran

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Jayachandran

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

All Works

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20 of 20 papers shown

Jayachandran, A., et al.. (2025). Data augmentation for machine learning assisted pesticide detection from SERS. Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy. 348(Pt 2). 127090–127090.

Jayachandran, A., et al.. (2024). Multi‐class brain tumor classification system in MRI images using cascades neural network. Computational Intelligence. 40(4). 1 indexed citations

Jayachandran, A., et al.. (2024). Multi-dimensional dense attention network for pixel-wise segmentation of optic disc in colour fundus images. Technology and Health Care. 32(6). 3829–3846. 1 indexed citations

Kannadhasan, S., et al.. (2023). Multi class robust brain tumor with hybrid classification using DTA algorithm. Heliyon. 10(1). e23610–e23610. 7 indexed citations

Jayachandran, A., et al.. (2023). Multi-stage Deep Convolutional Neural Network for Histopathological Analysis of Osteosarcoma. Neural Computing and Applications. 35(27). 20351–20364.

Jayachandran, A., et al.. (2023). Multi-dimensional cascades neural network models for the segmentation of retinal vessels in colour fundus images. Multimedia Tools and Applications. 82(27). 42927–42943. 10 indexed citations

Jayachandran, A., et al.. (2023). Microaneurysm classification system in color fundus images using auto‐weight dilated convolutional network. International Journal of Imaging Systems and Technology. 34(1). 2 indexed citations

Jayachandran, A., et al.. (2023). Deep CNN-based microaneurysm segmentation system in retinal images using multi-level features. Journal of Intelligent & Fuzzy Systems. 46(2). 4841–4857. 1 indexed citations

Jayachandran, A., et al.. (2023). Hybrid Behrens-Fisher- and Gray Contrast–Based Feature Point Selection for Building Detection from Satellite Images. Journal of Geovisualization and Spatial Analysis. 7(1). 7 indexed citations

10.

Jayachandran, A., et al.. (2018). Mixture Model Segmentation System for Parasagittal Meningioma brain Tumor Classification based on Hybrid Feature Vector. Journal of Medical Systems. 42(12). 251–251. 23 indexed citations

11.

Jayachandran, A., et al.. (2018). Severity analysis of diabetic retinopathy in retinal images using hybrid structure descriptor and modified CNNs. Measurement. 135. 762–767. 29 indexed citations

12.

Jayachandran, A., et al.. (2018). Textures and Intensity Histogram Based Retinal Image Classification System Using Hybrid Colour Structure Descriptor. Biomedical & Pharmacology Journal. 11(1). 577–582. 12 indexed citations

13.

Jayachandran, A., et al.. (2018). A new expert system based on hybrid colour and structure descriptor and machine learning algorithms for early glaucoma diagnosis. Multimedia Tools and Applications. 79(7-8). 5213–5224. 14 indexed citations

14.

Jayachandran, A. & R. Dhanasekaran. (2017). MULTI CLASS BRAIN TUMOR CLASSIFICATION OF MRI IMAGES USING HYBRID STRUCTURE DESCRIPTOR AND FUZZY LOGIC BASED RBF KERNEL SVM. Iranian journal of fuzzy systems. 14(3). 41–54. 15 indexed citations

15.

Jayachandran, A., et al.. (2015). Abnormality Segmentation and Classification of Multi-class Brain Tumor in MR Images Using Fuzzy Logic-Based Hybrid Kernel SVM. International Journal of Fuzzy Systems. 17(3). 434–443. 26 indexed citations

16.

Jayachandran, A. & R. Dhanasekaran. (2013). Brain Tumor Detection and Classification of MR Images Using Texture Features and Fuzzy SVM Classifier. Research Journal of Applied Sciences Engineering and Technology. 6(12). 2264–2269. 18 indexed citations

17.

Jayachandran, A. & R. Dhanasekaran. (2013). Brain Tumor Detection using Fuzzy Support Vector Machine Classification based on a Texton Co-occurrence Matrix. Journal of Imaging Science and Technology. 57(1). 10507–1. 12 indexed citations

18.

Jayachandran, A. & R. Dhanasekaran. (2013). Automatic detection of brain tumor in magnetic resonance images using multi‐texton histogram and support vector machine. International Journal of Imaging Systems and Technology. 23(2). 97–103. 30 indexed citations

19.

Jayachandran, A. & R. Dhanasekaran. (2012). Efficient demosaicking of color images using theoretic reconstruction technique. 282–286. 2 indexed citations

20.

Jayachandran, A., et al.. (2010). Fuzzy information system based digital image segmentation by edge detection. 2. 1–5. 2 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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