# Retinderdeep Singh

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/retinderdeep-singh/

## Facts

| Field | Value |
| --- | --- |
| Citations | 210 |
| Field | Brain Tumor Detection and Classification |
| h-index | 8 |
| i10-index | 5 |
| Last Known Institution | Chitkara University |
| OpenAlex ID | https://openalex.org/A5100612159 |
| ORCID iD | 0009-0003-9242-6454 |
| Works | 50 |

## Researcher papers

- [Ensemble Deep Learning Models for Enhanced Brain Tumor Classification by Leveraging ResNet50 and EfficientNet-B7 on High-Resolution MRI Images](https://scholariq.org/papers/ensemble-deep-learning-models-for-enhanced-brain-tumor-classification-by/)
- [Alzheimer Disease Detection using Deep Learning](https://scholariq.org/papers/alzheimer-disease-detection-using-deep-learning/)
- [Enhancing Accuracy in Detection of Meningioma Tumour Using RestNet 50 Deep CNN Model](https://scholariq.org/papers/enhancing-accuracy-in-detection-of-meningioma-tumour-using-restnet-50-deep-cnn/)
- [InceptionV3 in Medical Imaging: Enhancing Precision in Acute Lymphoblastic Leukaemia Diagnosis](https://scholariq.org/papers/inceptionv3-in-medical-imaging-enhancing-precision-in-acute-lymphoblastic/)
- [Revolutionary Changes in Acute Lymphoblastic Leukaemia Classification: The Impact of Deep Learning Convolutional Neural Networks](https://scholariq.org/papers/revolutionary-changes-in-acute-lymphoblastic-leukaemia-classification-the-impact/)
- [Advancing prenatal healthcare by explainable AI enhanced fetal ultrasound image segmentation using U-Net++ with attention mechanisms](https://scholariq.org/papers/advancing-prenatal-healthcare-by-explainable-ai-enhanced-fetal-ultrasound-image/)
- [Accuracy Enhancement in Detecting Pituitary Tumors Using Deep Learning](https://scholariq.org/papers/accuracy-enhancement-in-detecting-pituitary-tumors-using-deep-learning/)
- [Automatic Approach Based on Deep Learning for Tea Leaf Disease Detection](https://scholariq.org/papers/automatic-approach-based-on-deep-learning-for-tea-leaf-disease-detection/)
- [Enhancing Accuracy in Detection of Glioma Tumor Using DenseNet CNN](https://scholariq.org/papers/enhancing-accuracy-in-detection-of-glioma-tumor-using-densenet-cnn/)
- [Precision Kidney Disease Classification Using EfficientNet-B3 and CT Imaging](https://scholariq.org/papers/precision-kidney-disease-classification-using-efficientnet-b3-and-ct-imaging/)

## Researcher topics

- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Digital Imaging for Blood Diseases](https://scholariq.org/topics/digital-imaging-for-blood-diseases/)

## Researcher university

- [Chitkara University](https://scholariq.org/institutions/chitkara-university/)

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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.