machine learning for signal processing
Underwater Image Enhancement via a Fast yet Effective Traditional Method
Addressing underwater image challenges, our method MLLE enhances color, contrast, and details efficiently. Outperforming competitors, it processes 1024×1024×3 images in under 1s on a single CPU. Experiments show improved underwater image segmentation, keypoint detection, and saliency detection.
An Echo in Time: Tracing the Evolution of Beamforming Algorithms
Beamforming is a widely used signal processing technique to steer, shape, and focus an electromagnetic wave using an array of sensors toward a desired direction.
Model-Driven Deep Learning for MIMO Detection
In this blog, we investigate the model-driven deep learning for multiple input-multiple output (MIMO) detection. In particular, the MIMO detector is specially designed by unfolding an iterative algorithm and adding some trainable parameters.
