Presentation in group meeting of Prof. Michael Strano, Department of Chemical Engineering, Massachusetts Institute of Technology, USA and DiSTAP, Singapore-MIT Alliance for Research and Technology, Singapore.
Date: 23 February 2024
Neural network training requires complete data. We have introduced GapNet, which can train neural networks with incomplete data, using medical data. This approach can be generalized for integrating spectrum data across different frequency ranges, allowing the neural network to combine important information from diverse spectrum datasets.