Brayan Monroy
YOU?
Author Swipe
View article: DeepInverse: A Python package for solving imaging inverse problems with deep learning
DeepInverse: A Python package for solving imaging inverse problems with deep learning Open
International audience
View article: DeepInverse: A Python package for solving imaging inverse problems with deep learning
DeepInverse: A Python package for solving imaging inverse problems with deep learning Open
DeepInverse is an open-source PyTorch-based library for solving imaging inverse problems. The library covers all crucial steps in image reconstruction from the efficient implementation of forward operators (e.g., optics, MRI, tomography), …
View article: High Dynamic Range Modulo Imaging for Robust Object Detection in Autonomous Driving
High Dynamic Range Modulo Imaging for Robust Object Detection in Autonomous Driving Open
Object detection precision is crucial for ensuring the safety and efficacy of autonomous driving systems. The quality of acquired images directly influences the ability of autonomous driving systems to correctly recognize and respond to ot…
View article: Autoregressive High-Order Finite Difference Modulo Imaging: High-Dynamic Range for Computer Vision Applications
Autoregressive High-Order Finite Difference Modulo Imaging: High-Dynamic Range for Computer Vision Applications Open
High dynamic range (HDR) imaging is vital for capturing the full range of light tones in scenes, essential for computer vision tasks such as autonomous driving. Standard commercial imaging systems face limitations in capacity for well dept…
View article: Generalized Recorrupted-to-Recorrupted: Self-Supervised Learning Beyond Gaussian Noise
Generalized Recorrupted-to-Recorrupted: Self-Supervised Learning Beyond Gaussian Noise Open
Recorrupted-to-Recorrupted (R2R) has emerged as a methodology for training deep networks for image restoration in a self-supervised manner from noisy measurement data alone, demonstrating equivalence in expectation to the supervised square…
View article: Hadamard Row-Wise Generation Algorithm
Hadamard Row-Wise Generation Algorithm Open
In this paper, we introduce an efficient algorithm for generating specific Hadamard rows, addressing the memory demands of pre-computing the entire matrix. Leveraging Sylvester's recursive construction, our method generates the required $i…
View article: Designed Dithering Sign Activation for Binary Neural Networks
Designed Dithering Sign Activation for Binary Neural Networks Open
Binary Neural Networks emerged as a cost-effective and energy-efficient solution for computer vision tasks by binarizing either network weights or activations. However, common binary activations, such as the Sign activation function, abrup…
View article: Automated chronic wounds medical assessment and tracking framework based on deep learning
Automated chronic wounds medical assessment and tracking framework based on deep learning Open
Chronic wounds are a latent health problem worldwide, due to high incidence of diseases such as diabetes and Hansen. Typically, wound evolution is tracked by medical staff through visual inspection, which becomes problematic for patients i…
View article: JR2net: a joint non-linear representation and recovery network for compressive spectral imaging
JR2net: a joint non-linear representation and recovery network for compressive spectral imaging Open
Deep learning models are state-of-the-art in compressive spectral imaging (CSI) recovery. These methods use a deep neural network (DNN) as an image generator to learn non-linear mapping from compressed measurements to the spectral image. F…
View article: JR2net: A Joint Non-Linear Representation and Recovery Network for\n Compressive Spectral Imaging
JR2net: A Joint Non-Linear Representation and Recovery Network for\n Compressive Spectral Imaging Open
Deep learning models are state-of-the-art in compressive spectral imaging\n(CSI) recovery. These methods use a deep neural network (DNN) as an image\ngenerator to learn non-linear mapping from compressed measurements to the\nspectral image…