activity
20182022
most citedSRGAN: Training Dataset Matters

15 citations · 18 across the 4 of their papers we have counts for

collaborators

9 papers

eess.IV2022

Deep Learning Mixture-of-Experts Approach for Cytotoxic Edema Assessment in Infants and Children

Henok Ghebrechristos, Stence Nicholas, David Mirsky +7

This paper presents a deep learning framework for image classification aimed at increasing predictive performance for Cytotoxic Edema (CE) diagnosis in infants and children. The pr…

cs.CV20213 cited

GPRAR: Graph Convolutional Network based Pose Reconstruction and Action Recognition for Human Trajectory Prediction

Manh Huynh, Gita Alaghband

Prediction with high accuracy is essential for various applications such as autonomous driving. Existing prediction models are easily prone to errors in real-world settings where o…

cs.DC2020

High Performance Parallel Sort for Shared and Distributed Memory MIMD

Thoria Alghamdi, Gita Alaghband

We present four high performance hybrid sorting methods developed for various parallel platforms: shared memory multiprocessors, distributed multiprocessors, and clusters taking ad…

eess.IV2020

Generator From Edges: Reconstruction of Facial Images

Nao Takano, Gita Alaghband

Applications that involve supervised training require paired images. Researchers of single image super-resolution (SISR) create such images by artificially generating blurry input…

cs.CV2020

AOL: Adaptive Online Learning for Human Trajectory Prediction in Dynamic Video Scenes

Manh Huynh, Gita Alaghband

We present a novel adaptive online learning (AOL) framework to predict human movement trajectories in dynamic video scenes. Our framework learns and adapts to changes in the scene…

cs.CV2019

Trajectory Prediction by Coupling Scene-LSTM with Human Movement LSTM

Manh Huynh, Gita Alaghband

We develop a novel human trajectory prediction system that incorporates the scene information (Scene-LSTM) as well as individual pedestrian movement (Pedestrian-LSTM) trained simul…