Blog category
Self-Driving
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Unveiling Neural Mechanisms of Face Recognition: Insights from Unsupervised Deep Learning
This study uses unsupervised deep learning to uncover how neurons in the brain process and disentangle facial features for recognition.
Bridging Simulation and Reality: Generative AI in Driving Data Synthesis
This study explores using generative AI to synthesize driving data, enhancing autonomous vehicle training and bridging the Sim2Real gap.
Bridging Brain Activity and Facial Recognition: Insights from fMRI and Deep Generative Neural Networks
This study explores using deep generative neural networks to reconstruct facial images from fMRI patterns, linking brain activity to visual perception.
Exploring Synthetic Data Generation for Machine Learning
The paper explores synthetic data generation techniques, such as GANs and VAEs, addressing data scarcity and privacy concerns in machine learning.
SurfelGAN: Advancing Autonomous Driving with Realistic Sensor Data Synthesis
SurfelGAN synthesizes realistic sensor data for autonomous driving simulations, enhancing scene reconstruction with AI-generated camera images.
Enhancing Autonomous Driving with TL-GAN: Data Synthesis for Traffic Light Recognition
TL-GAN improves traffic light recognition by generating synthetic data, tackling data imbalance in autonomous driving systems.
Enhancing Autonomous Driving with Panacea: A New Approach to Video Generation
Panacea creates controllable videos for autonomous driving, improving data annotation.
Autonomous Driving Challenge
The Challenge of Autonomous Driving: Can Your AI See the Unseen?
Self-Driving
Advancing autonomous driving with synthetic data