Federated Learning with Rebalanced Dataset

With the widespread application of artificial intelligence, centralized machine learning approaches, which require access to users' local data, have raised concerns about data privacy. In response, federated learning, an architecture that aggregates models trained locally with local data, has been proposed. This approach addresses the data...

Unsupervised Wafer Map Failure Pattern Recognition with Contrastive Learning

This master’s thesis explores the application of Self-Supervised Contrastive Learning (SSCL), specifically the SimCLR algorithm, to enhance feature representation learning from Wafer Bin Maps (WBM) in the semiconductor manufacturing process. The motivation stems from the industry’s growing need for automated defect detection and root-cause...

Spiking Neural Networks Based Data Driven Control: An Illustration Using Cart-Pole Balancing Example

Machine learning can be effectively applied in control loops to robustly make optimal control decisions. There is increasing interest in using spiking neural networks (SNNs) as the apparatus for machine learning in control engineering, because SNNs can potentially offer high energy efficiency and new SNN-enabling neuromorphic hardwares are being...

Hierarchical Clustering Based State Abstraction In Reinforcement Learning

Reinforcement learning (RL) has grown tremendously over one and a half decades and is increasingly emerging in many real-life applications. However, the application of RL is still limited due to its low training efficiencies and surplus training cost. The sampling and computation complexity normally depends on the size of the state space and...

LightDigit: Embedded Deep Learning Empowered Fingertip Air-Writing with Ambient Light

This thesis introduces LightDigit, a recognition system for fingertip air-writing digits that enables low-cost, privacy-preserving, and in air interaction with pub- lic devices such as touchscreens. The current LightDigit prototype can input digits to public devices with a simple array of photodiodes and with ubiquitous ambient light in our...

Point Spread Function Estimation with Blind Deconvolution in Structured Illumination Microscopy

Structured illumination microscopy (SIM) is a kind of wide-field super resolution imaging technique which achieves the resolution improvement by exploiting the interference patterns to obtain the information out of the observable region in Fourier space. The resolution improvement in SIM is done by analyzing the obtained image and restored the...

People Detection from Overhead Cameras: A study of impact of occlusion on performance

During the last decades, people detection has received great attention in computer vision and pattern recognition because of its various applications. Though there are thousands of papers provide approaches for people detection, most of them focus on datasets from side view. People detection from overhead cameras, as an important situation for...