278 citations · 392 across the 10 of their papers we have counts for
10 papers
Transabdominal Fetal Oximetry via Diffuse Optics: Principled Analysis and Demonstration in Pregnant Ovine Models
Weitai Qian, Rishad Raiyan Joarder, Randall Fowler +7
Diffuse optics has the potential to offer a substantial advancement in fetal health monitoring via enabling continuous measurement of fetal blood oxygen saturation (fSpO). Aimi…
Deep Harmonic Finesse: Signal Separation in Wearable Systems with Limited Data
Mahya Saffarpour, Kourosh Vali, Weitai Qian +3
We present a method, referred to as Deep Harmonic Finesse (DHF), for separation of non-stationary quasi-periodic signals when limited data is available. The problem frequently aris…
Resource-Scalable CNN Synthesis for IoT Applications
Mohammad Motamedi, Felix Portillo, Mahya Saffarpour +2
State-of-the-art image recognition systems use sophisticated Convolutional Neural Networks (CNNs) that are designed and trained to identify numerous object classes. Such networks a…
Distill-Net: Application-Specific Distillation of Deep Convolutional Neural Networks for Resource-Constrained IoT Platforms
Mohammad Motamedi, Felix Portillo, Daniel Fong +1
Many Internet-of-Things (IoT) applications demand fast and accurate understanding of a few key events in their surrounding environment. Deep Convolutional Neural Networks (CNNs) ha…
A Design Space Exploration (DSE) on Non-Invasive Sensing of Bladder Filling Using Near Infrared Spectroscopy (NIRS)
Mahya Saffarpour, Soheil Ghiasi
Urinary Incontinence (UI) is a widespread medical condition that affects one person from every three or four Americans. Near-Infrared Spectroscopy (NIRS) is a non-invasive under-st…
A Data-Driven Approach to Pre-Operative Evaluation of Lung Cancer Patients
Oleksiy Budilovsky, Golnaz Alipour, Andre Knoesen +2
Lung cancer is the number one cause of cancer deaths. Many early stage lung cancer patients have resectable tumors; however, their cardiopulmonary function needs to be properly eva…
Cappuccino: Efficient Inference Software Synthesis for Mobile System-on-Chips
Mohammad Motamedi, Daniel Fong, Soheil Ghiasi
Convolutional Neural Networks (CNNs) exhibit remarkable performance in various machine learning tasks. As sensor-equipped Internet of Things (IoT) devices permeate into every aspec…
Fast and Energy-Efficient CNN Inference on IoT Devices
Mohammad Motamedi, Daniel Fong, Soheil Ghiasi
Convolutional Neural Networks (CNNs) exhibit remarkable performance in various machine learning tasks. As sensor-equipped internet of things (IoT) devices permeate into every aspec…
Hardware-oriented Approximation of Convolutional Neural Networks
Philipp Gysel, Mohammad Motamedi, Soheil Ghiasi
High computational complexity hinders the widespread usage of Convolutional Neural Networks (CNNs), especially in mobile devices. Hardware accelerators are arguably the most promis…
CNNdroid: GPU-Accelerated Execution of Trained Deep Convolutional Neural Networks on Android
Seyyed Salar Latifi Oskouei, Hossein Golestani, Matin Hashemi +1
Many mobile applications running on smartphones and wearable devices would potentially benefit from the accuracy and scalability of deep CNN-based machine learning algorithms. Howe…