Muneeza Azmat
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View article: Out-of-Distribution Detection using Synthetic Data Generation
Out-of-Distribution Detection using Synthetic Data Generation Open
Distinguishing in- and out-of-distribution (OOD) inputs is crucial for reliable deployment of classification systems. However, OOD data is typically unavailable or difficult to collect, posing a significant challenge for accurate OOD detec…
View article: SPRI: Aligning Large Language Models with Context-Situated Principles
SPRI: Aligning Large Language Models with Context-Situated Principles Open
Aligning Large Language Models to integrate and reflect human values, especially for tasks that demand intricate human oversight, is arduous since it is resource-intensive and time-consuming to depend on human expertise for context-specifi…
View article: Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management
Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management Open
Agriculture faces unprecedented challenges due to climate change, population growth, and water scarcity. These challenges highlight the need for efficient resource usage to optimize crop production. Conventional techniques for forecasting …
View article: A SWAT-based Reinforcement Learning Framework for Crop Management
A SWAT-based Reinforcement Learning Framework for Crop Management Open
Crop management involves a series of critical, interdependent decisions or actions in a complex and highly uncertain environment, which exhibit distinct spatial and temporal variations. Managing resource inputs such as fertilizer and irrig…
View article: Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management
Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management Open
Climate change, population growth, and water scarcity present unprecedented challenges for agriculture. This project aims to forecast soil moisture using domain knowledge and machine learning for crop management decisions that enable susta…
View article: Multi-class segmentation of brain tumor using Convolution Neural Network
Multi-class segmentation of brain tumor using Convolution Neural Network Open
In this report a fully Convolution Neural Network (CNN) architecture is used to segment multi-modal Brain Tumors from Magnetic Resonance (MR) images. Due to the challenges in manual segmentation, computerized brain tumor segmentation is on…