Splitting the Difference Between Deep and Shallow Solutions of Inverse Problems
Explores balancing compressed sensing and deep learning in computational imaging, showcasing Plenoxels for efficient photorealistic view synthesis without neural networks.
Computational Imaging - Deep Learning Approaches
Explore advanced computational imaging techniques with Jong Chul Ye from KAIST, covering innovative approaches in signal processing and image reconstruction.
GI Motility of the Small Intestine
Explore small intestine motility, including segmentation, peristalsis, and the ileocecal valve. Learn about crucial digestive processes and their impact on nutrient absorption and waste elimination.
Perception and Learning for Autonomous Driving - Part 1
Explore perception and learning for autonomous driving, covering sensor suites, deep neural networks, and object detection techniques in this comprehensive tutorial.
On Bayesian Models with Networks for Reconstruction and Detection
Explore Bayesian models with neural networks for MRI reconstruction and outlier detection in medical imaging, focusing on network-based priors and generative modeling approaches.
Geometric Understanding of Supervised and Unsupervised Deep Learning for Biomedical Image Reconstruction
Geometric understanding of deep learning for biomedical image reconstruction, exploring supervised and unsupervised approaches, with applications in various imaging modalities.
Deep Learning-Based MR Image Reconstruction and Contrast Conversion
Explore deep learning techniques for MR image reconstruction, parallel imaging, and contrast conversion, focusing on k-space and image space applications in medical imaging.
Deep Decoder: Concise Image Representations from Untrained Networks - Lecture 2
Explores untrained neural networks as image models, focusing on the Deep Decoder for efficient compression and denoising. Discusses theoretical foundations and compares performance to other approaches.
Gunnar Carlsson - Deep Learning and TDA
Explore deep learning's interaction with Topological Data Analysis, focusing on explainability and performance enhancement in neural networks and various data analysis applications.
Premonitions of Public Data for Private ML
Explore how public data pre-training enhances private machine learning, examining its impact on accuracy, zero-shot learning, and the future of privacy-preserving AI techniques.
Model-Based Deep Learning: Deep Equilibrium Models and Proximal Gradient Maps
Explore model-based deep learning, deep equilibrium models, and their applications in image recovery, focusing on robustness, safety, and efficiency in undersampled data scenarios.
Computational Imaging Systems and Optical Design - Webinar
Explore computational imaging systems, diffractive optics, and neural network-based reconstruction in this advanced signal processing webinar by Prof. Wolfgang Heidrich from KAUST.
SPACE Webinar Series: Adaptive Dynamic Scanning and Task-Driven Image Reconstruction
Prof. Bin Dong explores signal processing challenges, focusing on image reconstruction, deep learning applications, and task-driven approaches in computer vision and medical imaging.
Physics Matters - In Artificial Intelligence - Natural and Artificial Cognition
Explore natural and artificial cognition, machine learning, and computer vision applications in healthcare, research, and autonomous vehicles with Professor Kalle Åström.
Computational Imaging - Depth Estimation Techniques and Applications
Explore advanced techniques in computational imaging, focusing on depth estimation methods, stereo vision, and novel applications in 3D reconstruction and image synthesis.
Computational Imaging: Black Hole Shadows and Imaging Algorithms - Webinar
Explore computational imaging techniques for black hole visualization, featuring insights on imaging algorithms, bias avoidance, and telescope design optimization.
Computational Imaging Systems: From DiffuserCam to Neural Activity Tracking - Seminar 2
Explore computational imaging systems, focusing on DiffuserCam technology and its applications in 3D neural activity tracking. Learn about challenges and solutions in image reconstruction and processing.
How to Restore and Colorize Old Photos with AI - Stable Diffusion + ControlNet Tutorial
Learn to restore and colorize old photos using AI techniques like Stable Diffusion and ControlNet. This tutorial covers photo preparation, AI settings, refinement, and final adjustments for impressive results.
All Things VQGAN - VQ-VAE and GAN with Transformers and Codebook Interaction
Explore VQ-VAE and GAN integration with Transformers in VQGAN, focusing on codebook interaction and new image generation techniques.
Text to Image AI Models - Different Methodologies and How It Works
Explore various AI methodologies for text-to-image generation, including Autoregressive models, GANs, VQ-VAE Transformers, and Diffusion models. Learn their inner workings and compare advanced systems like DALL-E 2 and Google Imagen.
LIMoE- Learning Multiple Modalities with One Sparse Mixture-of-Experts Model
Explore LIMoE, a multimodal AI architecture processing images and text with sparse experts. Learn its internals, training, contrastive learning, behavior, and performance.