10 accepted papers
Hypertension is a leading risk factor for cardiovascular diseases. Traditional blood pressure monitoring methods are cumbersome and inadequate for continuous tracking, prompting the development of PPG-based cuffless blood pressure monitoring wearables. This study leverages deep learning models, incl…
Generative Adversarial Networks (GANs) have shown promise in augmenting datasets and boosting convolutional neural network (CNN) performance on image classification tasks. But they introduce more hyperparameters to tune as well as the need for additional time and computational power to train, supple…
We argue that learning a hierarchy of features in a hierarchical dataset requires lower layers to approach convergence faster than layers above them. We show that, if this assumption holds, we can analytically approximate the outcome of stochastic gradient descent (SGD) for each layer. We find that…
Recently, time-of-flight (ToF) sensors have emerged as a promising three-dimensional sensing technology that can be manufactured inexpensively in a compact size. However, current state-of-the-art ToF sensors suffer from low spatial resolution due to physical limitations in the fabrication process. I…
In this paper, the problem of automatic nonlinear unmixing of hyperspectral reflectance data using works of art as test cases is described. We use a deep neural network to decompose a given spectrum quantitatively to the abundance values of pure pigments. We show that adding another step to identify…
Deep Learning techniques and more specifically Generative Adversarial Networks (GANs) have recently been used for solving the video super-resolution (VSR) problem. In some of the published works, feature-based perceptual losses have also been used, resulting in promising results. While there has bee…
Multi-focus microscope (MFM) provides a way to obtain 3D information by simultaneously capturing multiple focal planes. The naive method for MFM reconstruction is to stack the sub-images with alignment. However, the resolution in the z-axis in this method is limited by the number of acquired focal p…
Video object segmentation targets segmenting a specific object throughout a video sequence when given only an annotated first frame. Recent deep learning based approaches find it effective to fine-tune a general-purpose segmentation model on the annotated frame using hundreds of iterations of gradie…
Multi-frame image super-resolution (SR) is an image processing technology applicable to any digital, pixilated camera that is limited, by construction, to a certain number of pixels. The objective of SR is to utilize signal processing to overcome the physical limitation and emulate the “capabilities…
Non-cosmic, non-Gaussian disturbances known as “glitches”, show up in gravitational-wave data of the Advanced Laser Interferometer Gravitational-wave Observatory, or aLIGO. In this paper, we propose a deep multi-view convolutional neural network to classify glitches automatically. The primary purpos…