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Found 8 papers, 2 papers with code
Fusing Convolutional Neural Network and Geometric Constraint for Image-based Indoor Localization
This paper proposes a new image-based localization framework that explicitly localizes the camera/robot by fusing Convolutional Neural Network (CNN) and sequential images' geometric constraints.
Face-to-Music Translation Using a Distance-Preserving Generative Adversarial Network with an Auxiliary Discriminator
Further, we discover that the distance preservation constraint in the generative adversarial model leads to reduced diversity in the translated audio samples, and propose the use of an auxiliary discriminator to enhance the diversity of the translations while using the distance preservation constraint.
Deep Sensory Substitution: Noninvasively Enabling Biological Neural Networks to Receive Input from Artificial Neural Networks
A generative adversarial network (GAN) is then used to find a distance preserving map from this metric space of feature vectors into the metric space defined by a target audio dataset equipped with either the Euclidean metric or a mel-frequency cepstrum-based psychoacoustic distance metric.
Combining Deep Learning with Geometric Features for Image based Localization in the Gastrointestinal Tract
Considering these, we propose a novel approach to combine DL method with traditional feature based approach to achieve better localization with small training data.
A Closed-Form Uncertainty Propagation in Non-Rigid Structure from Motion
In this paper, we present a statistical inference on the element-wise uncertainty quantification of the estimated deforming 3D shape points in the case of the exact low-rank SDP problem.
Uncertainty Quantification for Hyperspectral Image Denoising Frameworks based on Low-rank Matrix Approximation
Sliding-window based low-rank matrix approximation (LRMA) is a technique widely used in hyperspectral images (HSIs) denoising or completion.
QoS and Jamming-Aware Wireless Networking Using Deep Reinforcement Learning
The problem of quality of service (QoS) and jamming-aware communications is considered in an adversarial wireless network subject to external eavesdropping and jamming attacks.
Method for an unbinned measurement of the $q^2$ dependent decay amplitudes of $\bar{B}^{0}\to \bar{K}^{*0}μ^+μ^-$ decays
A method for determining the $q^2$ dependent $\bar{K}^{*0}$ spin amplitudes of $\bar{B}^{0}\to \bar{K}^{*0}\mu^+\mu^-$ decays through a maximum likelihood fit to data is presented.
High Energy Physics - Phenomenology High Energy Physics - Experiment
