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   Articles with "map estimation" as a keyword



Joint Transmission Map Estimation and Dehazing Using Deep Networks

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recommendations! Published in 2020 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2019.2912145

Abstract: Single image haze removal is an extremely challenging problem due to its inherent ill-posed nature. Several prior-based and learning-based methods have been proposed in the literature to solve this problem and they have achieved visually… read more here.

Keywords: joint transmission; estimation dehazing; transmission map; transmission ... See more keywords

F2CENet: Single-Image Object Counting Based on Block Co-Saliency Density Map Estimation

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recommendations! Published in 2024 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2024.3449070

Abstract: This paper presents a novel single-image object counting method based on block co-saliency density map estimation, called free-to-count everything network (F2CENet). Image block co-saliency attention is introduced to promote density estimation adaptation, allowing to input… read more here.

Keywords: density map; saliency; block; density ... See more keywords

Unification of MAP Estimation and Marginal Inference in Recurrent Neural Networks

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recommendations! Published in 2018 at "IEEE Transactions on Neural Networks and Learning Systems"

DOI: 10.1109/tnnls.2018.2805813

Abstract: Numerous experimental data show that human brain can represent probability distributions and perform Bayesian inference. However, it remains unclear how the brain implements probabilistic inference in the form of neural circuits. Several models have been… read more here.

Keywords: map estimation; recurrent neural; marginal inference; estimation marginal ... See more keywords

EfficientNet-B0 Based Monocular Dense-Depth Map Estimation

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recommendations! Published in 2021 at "Traitement du Signal"

DOI: 10.18280/ts.380524

Abstract: Monocular depth estimation is a hot research topic in autonomous car driving. Deep convolution neural networks (DCNN) comprising encoder and decoder with transfer learning are exploited in the proposed work for monocular depth map estimation… read more here.

Keywords: map estimation; depth map; efficientnet based; depth ... See more keywords