@inproceedings {Virtual Event, title = {MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time}, year = {2020}, month = {07/2020}, address = {Virtual Event}, abstract = {

Monocular multi-object detection and localization in 3D space has been proven to be a challenging task. The MoNet3D algorithm is a novel and effective framework that can predict the 3D position of each object in a monocular image and draw a 3D bounding box for each object. The MoNet3D method incorporates prior knowledge of the spatial geometric correlation of neighboring objects into the deep neural network training process to improve the accuracy of 3D object localization. Experiments on the KITTI dataset show that the accuracy for predicting the depth and horizontal coordinates of objects in 3D space can reach 96.25\% and 94.74\%, respectively. Moreover, the method can realize the real-time image processing at 27.85 FPS, showing promising potential for embedded advanced driving assistance system applications. Our code is publicly available at

}, keywords = {psclab}, author = {Xichuan Zhou and Yicong Peng and Chunqiao Long and Fengbo Ren and Cong Shi} } @inproceedings {29, title = {mCOPD: Mobile Phone Based Lung Function Diagnosis and Exercise System for COPD}, year = {2013}, month = {05/2013}, publisher = {ACM}, abstract = {

COPD (Chronic Obstructive Pulmonary Disease) is a serious lung disease that causes difficulty in breathing. COPD patients require lung function examinations and perform breathing exercises on a regular basis in order to manage and be more aware of their health status. In this paper, we designed and developed a mobile-phone based system for lung function diagnosis, called mCOPD. Besides enabling accurate COPD examinations at home, the mCOPD system also offers a video-game based guidance system for breathing exercises. We evaluated mCOPD in controlled and uncontrolled environments with 40 subjects. The experimental results show that our system is a promising tool for remote medical treatment of COPD.

}, keywords = {psclab}, url = {http://dl.acm.org/citation.cfm?id=2504383}, author = {Xu, Wenyao and Huang, Ming-Chun and Liu, Jason J and Ren, Fengbo and Shen, Xinchen and Liu, Xiao and Sarrafzadeh, Majid} } @article {277, title = {MemBuilder: a web-based graphical interface to build heterogeneously mixed membrane bilayers for the GROMACS biomolecular simulation program}, journal = {Bioinformatics}, volume = {30}, year = {2013}, pages = {439{\textendash}441}, abstract = {

Motivation:\ Molecular dynamics (MD) simulations have had a profound impact on studies of membrane proteins during past two decades, but the accuracy of MD simulations of membranes is limited by the quality of membrane models and the applied force fields. Membrane models used in MD simulations mostly contain one kind of lipid molecule. This is far from reality, for biological membranes always contain more than one kind of lipid molecule. Moreover, the lipid composition and their distribution are functionally important. As a result, there is a necessity to prepare more realistic lipid membranes containing different types of lipids at physiological concentrations.

Results:\ To automate and simplify the building process of heterogeneous lipid bilayers as well as providing molecular topologies for included lipids based on both united and all-atom force fields, we provided MemBuilder as a web-based graphical user interface.

Availability and implementation:\ MemBuilder is a free web server available\ 

}, keywords = {other}, author = {Ghahremanpour, Mohammad Mehdi and Arab, Seyed Shahriar and Biookaghazadeh, Saman and Zhang, Jin and van der Spoel, David} }