Covers the conversion of analog signals to digital, data compression, and signal reconstruction, highlighting the significance of signal processing in communication systems.
Explores image compression through various approaches like pixel and block level compression, Discrete Cosine Transform, quantization, and entropy coding.
Covers Principal Component Analysis for dimensionality reduction, exploring its applications, limitations, and importance of choosing the right components.
Explores the provable benefits of overparameterization in model compression, emphasizing the efficiency of deep neural networks and the importance of retraining for improved performance.
Presents an all-analog photoelectronic chip for high-speed vision tasks, addressing challenges in classical computation and proposing a hybrid optical-electrical framework.
