Search Results - "Prokhorov, Danil"

Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene by Jun Li, Xue Mei, Prokhorov, Danil, Dacheng Tao

“…Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing…”
Get full text

Feature Pyramid and Hierarchical Boosting Network for Pavement Crack Detection by Yang, Fan, Zhang, Lei, Yu, Sijia, Prokhorov, Danil, Mei, Xue, Ling, Haibin

“…Pavement crack detection is a critical task for insuring road safety. Manual crack detection is extremely time-consuming. Therefore, an automatic road crack…”
Get full text

Tracking via Robust Multi-task Multi-view Joint Sparse Representation by Zhibin Hong, Xue Mei, Prokhorov, Danil, Dacheng Tao

“…Combining multiple observation views has proven beneficial for tracking. In this paper, we cast tracking as a novel multi-task multi-view sparse learning…”
Get full text

Approximation with random bases: Pro et Contra by Gorban, Alexander N., Tyukin, Ivan Yu, Prokhorov, Danil V., Sofeikov, Konstantin I.

“…In this work we discuss the problem of selecting suitable approximators from families of parameterized elementary functions that are known to be dense in a…”
Get full text

Model-Free Dual Heuristic Dynamic Programming by Zhen Ni, Haibo He, Xiangnan Zhong, Prokhorov, Danil V.

“…Model-based dual heuristic dynamic programming (MB-DHP) is a popular approach in approximating optimal solutions in control problems. Yet, it usually requires…”
Get full text

GrDHP: A General Utility Function Representation for Dual Heuristic Dynamic Programming by Zhen Ni, Haibo He, Dongbin Zhao, Xin Xu, Prokhorov, Danil V.

“…A general utility function representation is proposed to provide the required derivable and adjustable utility function for the dual heuristic dynamic…”
Get full text

Merging in Congested Freeway Traffic Using Multipolicy Decision Making and Passive Actor-Critic Learning by Nishi, Tomoki, Doshi, Prashant, Prokhorov, Danil

“…Merging in congested freeway traffic is a significant challenge toward realizing fully automated (level 4) driving. Merging vehicles need to decide not only…”
Get full text

Robust acoustic directional sensing enabled by synergy between resonator-based sensor and deep learning by Yu, Ziqi, Li, Xiaopeng, Jung, Hojung, Harada, Masahiro, Prokhorov, Danil, Lee, Taehwa

“…We demonstrate enhanced acoustic sensing arising from the synergy between resonator-based acoustic sensor and deep learning. We numerically verify that both…”
Get full text

Cross-Domain Traffic Scene Understanding: A Dense Correspondence-Based Transfer Learning Approach by Di, Shuai, Zhang, Honggang, Li, Chun-Guang, Mei, Xue, Prokhorov, Danil, Ling, Haibin

“…Understanding traffic scene images taken from vehicle mounted cameras is important for high-level tasks, such as advanced driver assistance systems and…”
Get full text

Toyota Prius HEV neurocontrol and diagnostics by Prokhorov, Danil V.

“…A neural network controller for improved fuel efficiency of the Toyota Prius hybrid electric vehicle is proposed. A new method to detect and mitigate a battery…”
Get full text

Force Anticipation and Its Potential Implications on Feedforward and Feedback Human Motor Control by Kimpara, Hideyuki, Mbanisi, Kenechukwu C., Li, Zhi, Troy, Karen L., Prokhorov, Danil, Gennert, Michael A.

“…Objective To investigate the effects of human force anticipation, we conducted an experimental load-pushing task with diverse combinations of informed and…”
Get full text

Training Recurrent Neurocontrollers for Real-Time Applications by Prokhorov, D.V.

“…In this paper, we introduce a new approach to train recurrent neurocontrollers for real-time applications. We begin with training a recurrent neurocontroller…”
Get full text

Recurrent neural network based prediction of epileptic seizures in intra- and extracranial EEG by Petrosian, Arthur, Prokhorov, Danil, Homan, Richard, Dasheiff, Richard, Wunsch, Donald

“…Predicting the onset of epileptic seizure is an important and difficult biomedical problem, which has attracted substantial attention of the intelligent…”
Get full text

Training Recurrent Neurocontrollers for Robustness With Derivative-Free Kalman Filter by Prokhorov, D.V.

“…We are interested in training neurocontrollers for robustness on discrete-time models of physical systems. Our neurocontrollers are implemented as recurrent…”
Get full text

Model-Free Real-Time EV Charging Scheduling Based on Deep Reinforcement Learning by Wan, Zhiqiang, Li, Hepeng, He, Haibo, Prokhorov, Danil

“…Driven by the recent advances in electric vehicle (EV) technologies, EVs have become important for smart grid economy. When EVs participate in demand response…”
Get full text

Stability analysis of discrete-time recurrent neural networks by Barabanov, N.E., Prokhorov, D.V.

“…We address the problem of global Lyapunov stability of discrete-time recurrent neural networks (RNNs) in the unforced (unperturbed) setting. It is assumed that…”
Get full text

Design and fabrication of multi-pouch inflatable holding structure with higher payload by Song, Yuyang, Gandhi, Umesh, Prokhorov, Danil V

“…Multi-pouch inflatable holding structure are designed using commercial finite element analysis (FEA) and developed to achieve higher payload using high…”
Get full text

Simple and conditioned adaptive behavior from Kalman filter trained recurrent networks by Feldkamp, Lee A., Prokhorov, Danil V., Feldkamp, Timothy M.

“…We illustrate the ability of a fixed-weight neural network, trained with Kalman filter methods, to perform tasks that are usually entrusted to an explicitly…”
Get full text

A Convolutional Learning System for Object Classification in 3-D Lidar Data by Prokhorov, Danil

“…In this brief, a convolutional learning system for classification of segmented objects represented in 3-D as point clouds of laser reflections is proposed…”
Get full text

Training Winner-Take-All Simultaneous Recurrent Neural Networks by Xindi Cai, Prokhorov, D.V., Wunsch, D.C.

“…The winner-take-all (WTA) network is useful in database management, very large scale integration (VLSI) design, and digital processing. The synthesis procedure…”
Get full text