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Shakhnoza Muksimova

Professor

Gachon University

South Korea

Research Interests

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Professors in South Korea Professors in Medical Imaging Medical Imaging professors in South Korea

About

Shakhnoza Muksimova is an Assistant Professor at Gachon University in South Korea. Her research interests encompass advanced topics in deep learning and its applications in various fields, including agriculture, biomedical imaging, and environmental monitoring. Recent publications highlight her work on UAV-based detection systems, image classification frameworks, and innovative approaches to disease detection and diagnosis, showcasing her commitment to applying AI technologies for societal benefit.

Articles (20)

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Shakhnoza Muksimova

Research Interests

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Articles (20)

Differentiable Resolution Allocation for Tiny Object Detection in UAV Imagery

Detecting Wildfire Smoke Onset from Fixed View Camera Networks

Unified Temporal–Spectral–Spatial Modeling for Robust and Generalizable Motor Imagery Brain–Computer Interfaces

Lightweight adaptive AI for novel real-time facial expression recognition

Breaking Barriers in Fire Detection – A Lightweight Model for Forest Surveillance

Video Captioning with Spatio-Temporal Graph Transformers

A Unified Transformer Model for Simultaneous Cotton Boll Detection, Pest Damage Segmentation, and Phenological Stage Classification from UAV Imagery

DeepBiteNet: A Lightweight Ensemble Framework for Multiclass Bug Bite Classification Using Image-Based Deep Learning

Empowering Smallholder Farmers with UAV-Based Early Cotton Disease Detection Using AI

Lightweight Transformer with Adaptive Rotational Convolutions for Aerial Object Detection

Lightweight Evolving U-Net for Next-Generation Biomedical Imaging

Lightweight Fire Detection in Tunnel Environments

Multi-Modal Fusion and Longitudinal Analysis for Alzheimer’s Disease Classification Using Deep Learning

Advanced Insect Detection Network for UAV-Based Biodiversity Monitoring

MBGPIN: Multi-Branch Generative Prior Integration Network for Super-Resolution Satellite Imagery

Force Map-Enhanced Segmentation of a Lightweight Model for the Early Detection of Cervical Cancer

Lightweight Deep Learning Model for Fire Classification in Tunnels

GazeCapsNet: A Lightweight Gaze Estimation Framework

RL-Cervix.Net: A Hybrid Lightweight Model Integrating Reinforcement Learning for Cervical Cell Classification

Cross-Modal Transformer-Based Streaming Dense Video Captioning with Neural ODE Temporal Localization

Collaborators (4)

Heung Seok Jeon

Halimjon Khujamatov

Abror Buriboev

Sabina Umirzakova

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