# University of Engineering and Technology Taxila

**Type:** Institutions  
**Canonical URL:** https://scholariq.org/institutions/university-of-engineering-and-technology-taxila/

## Facts

| Field | Value |
| --- | --- |
| Avg h-index | 21 |
| Citations | 277,164 |
| City | Rawalpindi |
| Country | PK |
| Description | University of Engineering and Technology Taxila is a research organisation in Rawalpindi, PK. OpenAlex records 7,173 works and 277,164 citations for it. 1,972 researchers list it as their most recent affiliation. |
| Homepage | http://www.uettaxila.edu.pk/ |
| OpenAlex ID | https://openalex.org/I173207729 |
| Researchers | 1,972 |
| ROR ID | https://ror.org/03v00ka07 |
| Type | education |
| Wikidata ID | https://www.wikidata.org/wiki/Q7895379 |
| Works | 7,173 |

## University papers

- [Deepfakes generation and detection: state-of-the-art, open challenges, countermeasures, and way forward](https://scholariq.org/papers/deepfakes-generation-and-detection-state-of-the-art-open-challenges/)
- [A novel deep learning method for detection and classification of plant diseases](https://scholariq.org/papers/a-novel-deep-learning-method-for-detection-and-classification-of-plant-diseases/)
- [Prediction of Heart Disease Using Deep Convolutional Neural Networks](https://scholariq.org/papers/prediction-of-heart-disease-using-deep-convolutional-neural-networks/)
- [A Novel Deep Learning Method for Recognition and Classification of Brain Tumors from MRI Images](https://scholariq.org/papers/a-novel-deep-learning-method-for-recognition-and-classification-of-brain-tumors/)
- [Detection of Diabetic Eye Disease from Retinal Images Using a Deep Learning Based CenterNet Model](https://scholariq.org/papers/detection-of-diabetic-eye-disease-from-retinal-images-using-a-deep-learning/)
- [A robust deep learning approach for tomato plant leaf disease localization and classification](https://scholariq.org/papers/a-robust-deep-learning-approach-for-tomato-plant-leaf-disease-localization-and/)
- [A Novel and Effective Brain Tumor Classification Model Using Deep Feature Fusion and Famous Machine Learning Classifiers](https://scholariq.org/papers/a-novel-and-effective-brain-tumor-classification-model-using-deep-feature-fusion/)
- [MaizeNet: A Deep Learning Approach for Effective Recognition of Maize Plant Leaf Diseases](https://scholariq.org/papers/maizenet-a-deep-learning-approach-for-effective-recognition-of-maize-plant-leaf/)
- [Artificial Intelligence-Based Drone System for Multiclass Plant Disease Detection Using an Improved Efficient Convolutional Neural Network](https://scholariq.org/papers/artificial-intelligence-based-drone-system-for-multiclass-plant-disease/)
- [Melanoma segmentation: A framework of improved <scp>DenseNet77</scp> and <scp>UNET</scp> convolutional neural network](https://scholariq.org/papers/melanoma-segmentation-a-framework-of-improved-scp-densenet77-scp-and-scp-unet/)
- [Efficient attention-based CNN network (EANet) for multi-class maize crop disease classification](https://scholariq.org/papers/efficient-attention-based-cnn-network-eanet-for-multi-class-maize-crop-disease/)

## University researchers

- [Momina Masood](https://scholariq.org/researchers/momina-masood/)

## University top topics

Showing 8 of 24.

- [Innovative concrete reinforcement materials](https://scholariq.org/topics/innovative-concrete-reinforcement-materials/)
- [Antenna Design and Analysis](https://scholariq.org/topics/antenna-design-and-analysis/)
- [Nanofluid Flow and Heat Transfer](https://scholariq.org/topics/nanofluid-flow-and-heat-transfer/)
- [Concrete and Cement Materials Research](https://scholariq.org/topics/concrete-and-cement-materials-research/)
- [Solar Thermal and Photovoltaic Systems](https://scholariq.org/topics/solar-thermal-and-photovoltaic-systems/)
- [Heat Transfer Mechanisms](https://scholariq.org/topics/heat-transfer-mechanisms/)
- [Heat Transfer and Optimization](https://scholariq.org/topics/heat-transfer-and-optimization/)
- [Smart Grid Energy Management](https://scholariq.org/topics/smart-grid-energy-management/)

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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.