Stochastic differential equations on noncompact manifolds: moment stability and its topological consequences. (arXiv:1911.07900v1 [math.PR])

In this paper we discuss the stability of stochastic differential equations and the interplay between the moment stability of a SDE and the topology of the underlying manifold. Sufficient and necessary conditions are given for the moment stability of a SDE in terms of the coefficients. Finally we prove a vanishing result for the fundamental…

Deep Learning Captures More Accurate Diffusion Fiber Orientations Distributions than Constrained Spherical Deconvolution. (arXiv:1911.07927v1 [eess.IV])

Confocal histology provides an opportunity to establish intra-voxel fiber orientation distributions that can be used to quantitatively assess the biological relevance of diffusion weighted MRI models, e.g., constrained spherical deconvolution (CSD). Here, we apply deep learning to investigate the potential of single shell diffusion weighted MRI to explain histologically observed fiber orientation distributions (FOD) and…

A Smartphone-Based Skin Disease Classification Using MobileNet CNN. (arXiv:1911.07929v1 [cs.CV])

The MobileNet model was used by applying transfer learning on the 7 skin diseases to create a skin disease classification system on Android application. The proponents gathered a total of 3,406 images and it is considered as imbalanced dataset because of the unequal number of images on its classes. Using different sampling method and preprocessing…

Fitness Done Right: a Real-time Intelligent Personal Trainer for Exercise Correction. (arXiv:1911.07935v1 [cs.CV])

Keeping fit has been increasingly important for people nowadays. However, people may not get expected exercise results without following professional guidance while hiring personal trainers is expensive. In this paper, an effective real-time system called Fitness Done Right (FDR) is proposed for helping people exercise correctly on their own. The system includes detecting human body…

Improving Universal Sound Separation Using Sound Classification. (arXiv:1911.07951v1 [cs.SD])

Deep learning approaches have recently achieved impressive performance on both audio source separation and sound classification. Most audio source separation approaches focus only on separating sources belonging to a restricted domain of source classes, such as speech and music. However, recent work has demonstrated the possibility of “universal sound separation”, which aims to separate acoustic…

Alternating Between Spectral and Spatial Estimation for Speech Separation and Enhancement. (arXiv:1911.07953v1 [cs.SD])

This work investigates alternation between spectral separation using masking-based networks and spatial separation using multichannel beamforming. In this framework, the spectral separation is performed using a mask-based deep network. The result of mask-based separation is used, in turn, to estimate a spatial beamformer. The output of the beamformer is fed back into another mask-based separation…

ISP4ML: Understanding the Role of Image Signal Processing in Efficient Deep Learning Vision Systems. (arXiv:1911.07954v1 [eess.IV])

Convolutional neural networks (CNNs) are now predominant components in a variety of computer vision (CV) systems. These systems typically include an image signal processor (ISP), even though the ISP is traditionally designed to produce images that look appealing to humans. In CV systems, it is not clear what the role of the ISP is, or…