# Sukadev Meher

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/sukadev-meher/

## Facts

| Field | Value |
| --- | --- |
| Citations | 2,173 |
| Field | Image and Signal Denoising Methods |
| h-index | 22 |
| i10-index | 45 |
| Last Known Institution | National Institute of Technology Rourkela |
| OpenAlex ID | https://openalex.org/A5037663112 |
| ORCID iD | 0000-0003-4397-3139 |
| Works | 122 |

## Researcher papers

- [An efficient deep Convolutional Neural Network based detection and classification of Acute Lymphoblastic Leukemia](https://scholariq.org/papers/an-efficient-deep-convolutional-neural-network-based-detection-and/)
- [An efficient deep learning scheme to detect breast cancer using mammogram and ultrasound breast images](https://scholariq.org/papers/an-efficient-deep-learning-scheme-to-detect-breast-cancer-using-mammogram-and/)
- [High accuracy hybrid CNN classifiers for breast cancer detection using mammogram and ultrasound datasets](https://scholariq.org/papers/high-accuracy-hybrid-cnn-classifiers-for-breast-cancer-detection-using-mammogram/)
- [A Systematic Review on Recent Advancements in Deep and Machine Learning Based Detection and Classification of Acute Lymphoblastic Leukemia](https://scholariq.org/papers/a-systematic-review-on-recent-advancements-in-deep-and-machine-learning-based/)
- [An Efficient Blood-Cell Segmentation for the Detection of Hematological Disorders](https://scholariq.org/papers/an-efficient-blood-cell-segmentation-for-the-detection-of-hematological/)
- [An Efficient Detection and Classification of Acute Leukemia Using Transfer Learning and Orthogonal Softmax Layer-Based Model](https://scholariq.org/papers/an-efficient-detection-and-classification-of-acute-leukemia-using-transfer/)
- [A Review of Automated Methods for the Detection of Sickle Cell Disease](https://scholariq.org/papers/a-review-of-automated-methods-for-the-detection-of-sickle-cell-disease/)
- [Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms](https://scholariq.org/papers/recent-advancements-in-machine-learning-and-deep-learning-based-breast-cancer/)
- [Detection of Moving Objects Using Fuzzy Color Difference Histogram Based Background Subtraction](https://scholariq.org/papers/detection-of-moving-objects-using-fuzzy-color-difference-histogram-based/)
- [A lightweight deep learning system for automatic detection of blood cancer](https://scholariq.org/papers/a-lightweight-deep-learning-system-for-automatic-detection-of-blood-cancer/)
- [Hybrid Deep Learning Framework for Multi-Class Plant Disease Classification and Detection](https://scholariq.org/papers/hybrid-deep-learning-framework-for-multi-class-plant-disease-classification-and/)

## Researcher topics

- [Image and Signal Denoising Methods](https://scholariq.org/topics/image-and-signal-denoising-methods/)
- [Advanced Image Processing Techniques](https://scholariq.org/topics/advanced-image-processing-techniques/)
- [Video Surveillance and Tracking Methods](https://scholariq.org/topics/video-surveillance-and-tracking-methods/)
- [Advanced Vision and Imaging](https://scholariq.org/topics/advanced-vision-and-imaging/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)

## Researcher university

- [National Institute of Technology Rourkela](https://scholariq.org/institutions/national-institute-of-technology-rourkela/)

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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.