A5103126714- Autonomous Vehicle Technology and Safety
- Advanced Neural Network Applications
- Traffic and Road Safety
- Remote Sensing and LiDAR Applications
- Genetics, Aging, and Longevity in Model Organisms
- Advanced Wireless Communication Techniques
- Wireless Communication Security Techniques
- Advanced MIMO Systems Optimization
- Stochastic processes and financial applications
- Sparse and Compressive Sensing Techniques
- Monetary Policy and Economic Impact
- Vehicle License Plate Recognition
- Health disparities and outcomes
- Data Management and Algorithms
- Image Retrieval and Classification Techniques
- Health and Well-being Studies
- Human-Automation Interaction and Safety
- Optical Wireless Communication Technologies
- Satellite Communication Systems
- Financial Risk and Volatility Modeling
- Face and Expression Recognition
- Traffic Prediction and Management Techniques
- Cooperative Communication and Network Coding
Mälardalen University
2024
Shahid Beheshti University
2017-2022
Sharif University of Technology
2012
Adaptive channel coding and power control for practical free-space optical communication systems are proposed in this paper. Particularly, we first assume that the state information (CSI) is perfectly known at transmitter, propose adaptive transmission schemes which rate adjusted either independently or jointly with transmit according to conditions. Moreover, an optimization problem developed attain consumption minimization under free space (FSO) constraints, i.e., target bit-error rate,...
Autonomous driving systems are a rapidly evolving technology. Trajectory prediction is critical component of autonomous that enables safe navigation by anticipating the movement surrounding objects. Lidar point-cloud data provide 3D view solid objects ego-vehicle. Hence, trajectory using performs better than 2D RGB cameras due to providing distance between target object and However, processing costly complicated process, state-of-the-art predictions suffer from slow erroneous predictions....
In this paper, we consider a broadband secondary transmitter-receiver pair which interferes with N narrowband primary users and study the effect of cognition cooperation on maximum stable throughput. our focus four transmission protocols as well two channel types, i.e., flat fading frequency selective fading. cooperative protocols, transmitter relays packets have not correctly decoded at receiver. The analysis includes random packet arrivals transmitters may impact Moreover, sensing errors...
Autonomous driving systems are a rapidly evolving technology that enables driverless car production. Trajectory prediction is critical component of autonomous systems, enabling cars to anticipate the movements surrounding objects for safe navigation. using Lidar point-cloud data performs better than 2D images due providing 3D information. However, processing more complicated and time-consuming images. Hence, state-of-the-art trajectory predictions suffer from slow erroneous predictions. This...
As the demand for autonomous driving (AD) systems has increased, enhancement of their safety become critically important. A fundamental capability AD is object detection and trajectory forecasting vehicles pedestrians around ego-vehicle, which essential preventing potential collisions. This study introduces Deep learning-based Acceleration-aware Trajectory (DAT) model, a deep approach forecasting, utilizing raw sensor measurements. DAT an end-to-end model that processes sequential data to...
Self-driving and autonomous cars are hot emerging technologies which can provide enormous impact in the near future. Since an important component of is vision processing, increasing interest for self-driving has motivated researchers to collect different relative image datasets. Hence, we a comprehensive dataset about road surface markings available Iran. In addition, evaluate conventional recognition rate. this paper, present novel extensive Persian Road Surface Markings (PRSM) with ground...
Continuous-time time series are widely used for modeling the realizations of those phenomena where it is theoretically possible to have observation at any point sampling domain. However, technical restrictions cause see such processes as discrete-time sample paths. We project time-domain observations into frequency-domain periodograms and employ Whittle's likelihood approximation make inference about parameters CARMA processes. The given under Bayesian paradigm some scenarios prior...