معرفی
Hao Cai is an Assistant Professor in the Department of Computer Science at St. Francis Xavier University. His research focuses on computer vision, machine learning, and image processing, with a particular emphasis on crowd counting, generative adversarial networks (GANs), and image quality assessment. He has developed innovative methods for multi-granularity crowd counting, scale-invariant feature aggregation, and disentangled representation learning in GAN frameworks. His work addresses challenges in real-world computer vision tasks such as density estimation, perceptual quality metrics, and 3D navigation for unmanned aerial vehicles (UAVs).
Dr. Cai’s research spans technical domains including deep learning architectures, stochastic aggregation networks, and adaptive convolutional neural networks. His contributions to multi-view stereopsis and visual homing algorithms have advanced robotics and autonomous systems. He has also explored sparse representation techniques for image quality evaluation, combining statistical analysis with perceptual models to enhance accuracy and efficiency.
His publications reflect a strong focus on practical applications of computer vision, from crowd analysis in urban environments to robust image quality assessment without reference images. Future work directions likely include further integration of adaptive learning strategies, scalable architectures, and interdisciplinary applications of vision systems.
