# Karunya University

**Type:** Institutions  
**Canonical URL:** https://scholariq.org/institutions/karunya-university/

## Facts

| Field | Value |
| --- | --- |
| Avg h-index | 8.3 |
| Citations | 264,070 |
| City | Coimbatore |
| Country | IN |
| Description | Karunya University is a research organisation in Coimbatore, IN. OpenAlex records 11,540 works and 264,070 citations for it. 6,342 researchers list it as their most recent affiliation. |
| Homepage | http://www.karunya.edu/ |
| OpenAlex ID | https://openalex.org/I119668213 |
| Researchers | 6,342 |
| ROR ID | https://ror.org/03k23nv15 |
| Type | education |
| Wikidata ID | https://www.wikidata.org/wiki/Q6373705 |
| Works | 11,540 |

## University papers

- [Determinants of employee engagement and their impact on employee performance](https://scholariq.org/papers/determinants-of-employee-engagement-and-their-impact-on-employee-performance/)
- [Change detection techniques for remote sensing applications: a survey](https://scholariq.org/papers/change-detection-techniques-for-remote-sensing-applications-a-survey/)
- [Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN)](https://scholariq.org/papers/classification-of-mammogram-images-using-multiscale-all-convolutional-neural/)
- [Optimum spectrum mask based medical image fusion using Gray Wolf Optimization](https://scholariq.org/papers/optimum-spectrum-mask-based-medical-image-fusion-using-gray-wolf-optimization/)
- [Image Processing Techniques for Analysis of Satellite Images for Historical Maps Classification—An Overview](https://scholariq.org/papers/image-processing-techniques-for-analysis-of-satellite-images-for-historical-maps/)
- [Plant disease classification using deep learning](https://scholariq.org/papers/plant-disease-classification-using-deep-learning/)
- [Modified Genetic Algorithm approaches for classification of abnormal Magnetic Resonance Brain tumour images](https://scholariq.org/papers/modified-genetic-algorithm-approaches-for-classification-of-abnormal-magnetic/)
- [Optimum laplacian wavelet mask based medical image using hybrid cuckoo search – grey wolf optimization algorithm](https://scholariq.org/papers/optimum-laplacian-wavelet-mask-based-medical-image-using-hybrid-cuckoo-search/)
- [Diabetic Retinopathy Diagnosis from Retinal Images Using Modified Hopfield Neural Network](https://scholariq.org/papers/diabetic-retinopathy-diagnosis-from-retinal-images-using-modified-hopfield/)
- [A dual stage adaptive thresholding (DuSAT) for automatic mass detection in mammograms](https://scholariq.org/papers/a-dual-stage-adaptive-thresholding-dusat-for-automatic-mass-detection-in/)
- [Knowledge Distillation-Driven Compressed CNN Model for Plant Disease Detection](https://scholariq.org/papers/knowledge-distillation-driven-compressed-cnn-model-for-plant-disease-detection/)

## University researchers

- [J. Anitha](https://scholariq.org/researchers/j-anitha/)
- [Arun C R](https://scholariq.org/researchers/arun-c-r/)
- [S. Immanuel Alex](https://scholariq.org/researchers/s-immanuel-alex/)

## University top topics

Showing 8 of 25.

- [IoT and Edge/Fog Computing](https://scholariq.org/topics/iot-and-edge-fog-computing/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Aluminum Alloys Composites Properties](https://scholariq.org/topics/aluminum-alloys-composites-properties/)
- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)
- [Antenna Design and Analysis](https://scholariq.org/topics/antenna-design-and-analysis/)
- [EEG and Brain-Computer Interfaces](https://scholariq.org/topics/eeg-and-brain-computer-interfaces/)
- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)
- [Artificial Intelligence in Healthcare](https://scholariq.org/topics/artificial-intelligence-in-healthcare/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.