Niyaz Ahmad Wani

Orcid: 0000-0002-7656-3374

According to our database1, Niyaz Ahmad Wani authored at least 17 papers between 2024 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Optimizing Deep Learning Models with Genetic Algorithms for Improved Classification and Identification of Wheat Leaf Diseases.
Int. J. Comput. Intell. Syst., December, 2026

Advanced LSTM frameworks for hotel bookings leveraging hippopotamus-inspired optimization.
Discov. Artif. Intell., December, 2026

Adaptive Edge Intelligence Framework for Resource-Constrained IoT in Consumer Electronics.
IEEE Trans. Consumer Electron., February, 2026

SFX-GAN: sustainable and explainable multi-modal spectral fusion for image dehazing in complex systems.
Complex Intell. Syst., 2026

2025
Optimized Federated Learning for Trustworthy Edge Decision-Making in IoT Consumer Electronics.
IEEE Trans. Consumer Electron., November, 2025

DASHES - Autonomous and Secure Framework for Connected Healthcare With Consumer Electronics.
IEEE Trans. Consumer Electron., November, 2025

Ameliorating Federated Learning Using Dynamic Inertia Weight-Based Advanced Particle Swarm Optimization for Consumer Electronic Devices.
IEEE Trans. Consumer Electron., November, 2025

Synergizing Fusion Modeling for Accurate Cardiac Prediction Through Explainable Artificial Intelligence.
IEEE Trans. Consumer Electron., February, 2025

Elevating Cloud Security With Advanced Trust Evaluation and Optimization of Hybrid Fireberg Technique.
IET Softw., 2025

DiaXplain: A transparent and interpretable artificial intelligence approach for Type-2 diabetes diagnosis through deep learning.
Comput. Electr. Eng., 2025

Next-Generation Automation in Neuro-Oncology: Advanced Neural Networks for MRI-Based Brain Tumor Segmentation and Classification.
IEEE Access, 2025

2024
<i>DeepXplainer</i>: An interpretable deep learning based approach for lung cancer detection using explainable artificial intelligence.
Comput. Methods Programs Biomed., January, 2024

Explainable AI-driven IoMT fusion: Unravelling techniques, opportunities, and challenges with Explainable AI in healthcare.
Inf. Fusion, 2024

Harnessing Fusion Modeling for Enhanced Breast Cancer Classification through Interpretable Artificial Intelligence and In-Depth Explanations.
Eng. Appl. Artif. Intell., 2024

ResMHA-Net: Enhancing Glioma Segmentation and Survival Prediction Using a Novel Deep Learning Framework.
Comput. Mater. Continua, 2024

Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network.
IEEE Access, 2024

TransResUNet: Revolutionizing Glioma Brain Tumor Segmentation Through Transformer-Enhanced Residual UNet.
IEEE Access, 2024


  Loading...