Muhammad Hamza Asad

According to our database, Muhammad Hamza Asad authored at least 10 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

HierVL: Semi-Supervised Segmentation leveraging Hierarchical Vision-Language Synergy with Dynamic Text-Spatial Query Alignment.

Numair Nadeem, Saeed Anwar, Muhammad Hamza Asad, Abdul Bais

CoRR, June, 2025

MaskAdapt: Unsupervised Geometry-Aware Domain Adaptation Using Multimodal Contextual Learning and RGB-Depth Masking.

Numair Nadeem, Muhammad Hamza Asad, Saeed Anwar, Abdul Bais

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

2024

Robust UDA for Crop and Weed Segmentation: Multi-scale Attention and Style-Adaptive Techniques.

Numair Nadeem, Muhammad Hamza Asad, Abdul Bais

Proceedings of the Computer Vision - ECCV 2024 Workshops, 2024

Improved Crop and Weed Detection with Diverse Data Ensemble Learning.

Muhammad Hamza Asad, Saeed Anwar, Abdul Bais

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Improved Crop and Weed Detection with Diverse Data Ensemble Learning in Agriculture.

Muhammad Hamza Asad, Saeed Anwar, Abdul Bais

CoRR, 2023

Soil Surface Texture Classification Using RGB Images Acquired Under Uncontrolled Field Conditions.

Ekunayo-Oluwabami Babalola, Muhammad Hamza Asad, Abdul Bais

IEEE Access, 2023

Detection and Mapping of Kochia Plants and Patches Using High-Resolution Ground Imagery and Satellite Data: Application of Machine Learning.

Muhammad Hamza Asad, Sajid Saleem, Abdul Bais

IEEE Access, 2023

2021

End to End Segmentation of Canola Field Images Using Dilated U-Net.

Hafiz Sami Ullah, Muhammad Hamza Asad, Abdul Bais

IEEE Access, 2021

2020

Crop and Weed Leaf Area Index Mapping Using Multi-Source Remote and Proximal Sensing.

Muhammad Hamza Asad, Abdul Bais

IEEE Access, 2020

2019

Weed Density Estimation Using Semantic Segmentation.

Muhammad Hamza Asad, Abdul Bais

Proceedings of the Image and Video Technology, 2019