Real-time embedded system of multi-task cnn for advanced driving assistance
M Miyama - International Journal of Advances in Signal and Image …, 2023 - xlescience.org
In this research, we've engineered a real-time embedded system for advanced driving
assistance. Our approach involves employing a multi-task Convolutional Neural Network …
assistance. Our approach involves employing a multi-task Convolutional Neural Network …
GP-NAS-ensemble: a model for NAS Performance Prediction
It is of great significance to estimate the performance of a given model architecture without
training in the application of Neural Architecture Search (NAS) as it may take a lot of time to …
training in the application of Neural Architecture Search (NAS) as it may take a lot of time to …
Real-Time Multi-Learning Deep Neural Network on an MPSoC-FPGA for Intelligent Vehicles: Harnessing Hardware Acceleration With Pipeline
This study introduces a new method to enhance ADAS's safety and error prevention
capabilities in intelligent vehicles. We address the significant computational and memory …
capabilities in intelligent vehicles. We address the significant computational and memory …
Generative modeling for multi-task visual learning
Generative modeling has recently shown great promise in computer vision, but it has mostly
focused on synthesizing visually realistic images. In this paper, motivated by multi-task …
focused on synthesizing visually realistic images. In this paper, motivated by multi-task …
Efficient Multi-task Learning for Road Scene Classification: Scene, Time, and Weather Predictions
R Prykhodchenko, P Skruch - 2024 IEEE 20th International …, 2024 - ieeexplore.ieee.org
This paper addresses the task of road scene classification by leveraging multi-task learning
(MTL) to improve model performance and computational efficiency. We employ the …
(MTL) to improve model performance and computational efficiency. We employ the …
Auto-VirtualNet: Cost-adaptive dynamic architecture search for multi-task learning
Multi-task learning (MTL) improves learning efficiency by solving multiple tasks
simultaneously compared to multiple instances of individual learning. However, despite its …
simultaneously compared to multiple instances of individual learning. However, despite its …