52 citations · 116 across the 16 of their papers we have counts for
16 papers
Online Fusion of Multi-resolution Multispectral Images with Weakly Supervised Temporal Dynamics
Haoqing Li, Bhavya Duvvuri, Ricardo Borsoi +4
Real-time satellite imaging has a central role in monitoring, detecting and estimating the intensity of key natural phenomena such as floods, earthquakes, etc. One important constr…
Recursive classification of satellite imaging time-series: An application to land cover mapping
Helena Calatrava, Bhavya Duvvuri, Haoqing Li +5
Despite the extensive body of literature focused on remote sensing applications for land cover mapping and the availability of high-resolution satellite imagery, methods for contin…
Recursive Estimation of User Intent from Noninvasive Electroencephalography using Discriminative Models
Niklas Smedemark-Margulies, Basak Celik, Tales Imbiriba +2
We study the problem of inferring user intent from noninvasive electroencephalography (EEG) to restore communication for people with severe speech and physical impairments (SSPI).…
Pregrasp Object Material Classification by a Novel Gripper Design with Integrated Spectroscopy
Nathaniel Hanson, Tarik Kelestemur, Deniz Erdogmus +1
Robots benefit from being able to classify objects they interact with or manipulate based on their material properties. This capability ensures fine manipulation of complex objects…
Neural Network-based OFDM Receiver for Resource Constrained IoT Devices
Nasim Soltani, Hai Cheng, Mauro Belgiovine +10
Orthogonal Frequency Division Multiplexing (OFDM)-based waveforms are used for communication links in many current and emerging Internet of Things (IoT) applications, including the…
Deep Learning Framework for Real-time Fetal Brain Segmentation in MRI
Razieh Faghihpirayesh, Davood Karimi, Deniz Erdogmus +1
Fetal brain segmentation is an important first step for slice-level motion correction and slice-to-volume reconstruction in fetal MRI. Fast and accurate segmentation of the fetal b…
Online multi-resolution fusion of space-borne multispectral images
Haoqing Li, Bhavia Duvviri, Ricardo Borsoi +4
Satellite imaging has a central role in monitoring, detecting and estimating the intensity of key natural phenomena. One important feature of satellite images is the trade-off betw…
Hybrid Neural Network Augmented Physics-based Models for Nonlinear Filtering
Tales Imbiriba, Ahmet Demirkaya, Jindřich Duník +3
In this paper we present a hybrid neural network augmented physics-based modeling (APBM) framework for Bayesian nonlinear latent space estimation. The proposed APBM strategy allows…
AutoTransfer: Subject Transfer Learning with Censored Representations on Biosignals Data
Niklas Smedemark-Margulies, Ye Wang, Toshiaki Koike-Akino +1
We provide a regularization framework for subject transfer learning in which we seek to train an encoder and classifier to minimize classification loss, subject to a penalty measur…
Equivariant Deep Dynamical Model for Motion Prediction
Bahar Azari, Deniz Erdoğmuş
Learning representations through deep generative modeling is a powerful approach for dynamical modeling to discover the most simplified and compressed underlying description of the…
EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals
Andac Demir, Toshiaki Koike-Akino, Ye Wang +2
Convolutional neural networks (CNN) have been frequently used to extract subject-invariant features from electroencephalogram (EEG) for classification tasks. This approach holds th…
On the Sample Complexity of Rank Regression from Pairwise Comparisons
Berkan Kadioglu, Peng Tian, Jennifer Dy +2
We consider a rank regression setting, in which a dataset of samples with features in is ranked by an oracle via pairwise comparisons. Specifically, there ex…
End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning
Mohammadreza Sharif, Deniz Erdogmus, Christopher Amato +1
State-of-the-art human-in-the-loop robot grasping is hugely suffered by Electromyography (EMG) inference robustness issues. As a workaround, researchers have been looking into inte…
Model-Based Deep Autoencoder Networks for Nonlinear Hyperspectral Unmixing
Haoqing Li, Ricardo Augusto Borsoi, Tales Imbiriba +3
Autoencoder (AEC) networks have recently emerged as a promising approach to perform unsupervised hyperspectral unmixing (HU) by associating the latent representations with the abun…
Inference of Upcoming Human Grasp Using EMG During Reach-to-Grasp Movement
Mo Han, Mehrshad Zandigohar, Sezen Yagmur Gunay +2
Electromyography (EMG) data has been extensively adopted as an intuitive interface for instructing human-robot collaboration. A major challenge of the real-time detection of human…
Multimodal Fusion of EMG and Vision for Human Grasp Intent Inference in Prosthetic Hand Control
Mehrshad Zandigohar, Mo Han, Mohammadreza Sharif +8
Objective: For transradial amputees, robotic prosthetic hands promise to regain the capability to perform daily living activities. Current control methods based on physiological si…