1 code implementation • 4 Apr 2025 • Zeyang Zheng, Arman Hosseini, Dong Chen, Omid Shoghli, Arsalan Heydarian
This study introduces a novel ground obstacle detection system for e-scooters, integrating an RGB camera, and a depth camera to enhance real-time road hazard detection.
no code implementations • 3 Apr 2025 • Seyed Hamidreza Nabaei, Ryan Lenfant, Viswajith Govinda Rajan, Dong Chen, Michael P. Timko, Bradford Campbell, Arsalan Heydarian
In the era of growing interest in healthy buildings and smart homes, the importance of sustainable, health conscious indoor environments is paramount.
no code implementations • 27 Mar 2025 • Seyed Hamidreza Nabaei, Zeyang Zheng, Dong Chen, Arsalan Heydarian
Unlike previous approaches, this framework combines RGB imagery, plant phenotyping data, and environmental factors such as temperature and humidity, to predict plant water stress in a controlled growth environment.
1 code implementation • 5 May 2024 • Dong Chen, Arman Hosseini, Arik Smith, Amir Farzin Nikkhah, Arsalan Heydarian, Omid Shoghli, Bradford Campbell
Electric scooters (e-scooters) have rapidly emerged as a popular mode of transportation in urban areas, yet they pose significant safety challenges.
1 code implementation • 2 Apr 2024 • Chen Yang, Yangfan He, Aaron Xuxiang Tian, Dong Chen, Jianhui Wang, Tianyu Shi, Arsalan Heydarian
To enhance the scene diversity and stochasticity, the historical trajectory data is first preprocessed into "Agent Move Statement" and encoded into latent space using Denoising Diffusion Probabilistic Models (DDPM) enhanced with Diffusion with Transformer (DiT) blocks.
no code implementations • 26 Mar 2023 • Alan Wang, Bradford Campbell, Arsalan Heydarian
Specifically, in this proof-of-concept exploration, we demonstrate the potential of physics-based simulation models to quantify the minimal number of positions necessary to capture sensitive inferences.
no code implementations • 7 Mar 2022 • Mahsa Pahlavikhah Varnosfaderani, Arsalan Heydarian, Farrokh Jazizadeh
Previous research has relied on CO$_2$ sensors and vision-based techniques to determine occupancy patterns.