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Found 7 papers, 0 papers with code
Weakly-supervised fire segmentation by visualizing intermediate CNN layers
Fire localization in images and videos is an important step for an autonomous system to combat fire incidents.
Attention on Classification for Fire Segmentation
The network is jointly trained for both segmentation and classification, leading to improvement in the performance of the single-task image segmentation methods, and the previous methods proposed for fire segmentation.
Image Restoration Using Conditional Random Fields and Scale Mixtures of Gaussians
This paper proposes a general framework for internal patch-based image restoration based on Conditional Random Fields (CRF).
External Patch-Based Image Restoration Using Importance Sampling
This paper introduces a new approach to patch-based image restoration based on external datasets and importance sampling.
Poisson Image Denoising Using Best Linear Prediction: A Post-processing Framework
In this paper, we address the problem of denoising images degraded by Poisson noise.
Class-specific image denoising using importance sampling
In this paper, we propose a new image denoising method, tailored to specific classes of images, assuming that a dataset of clean images of the same class is available.
Class-specific Poisson denoising by patch-based importance sampling
In this paper, we address the problem of recovering images degraded by Poisson noise, where the image is known to belong to a specific class.
