AIMC Topic: Algorithms

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Neural Shape Parsers for Constructive Solid Geometry.

IEEE transactions on pattern analysis and machine intelligence
Constructive solid geometry (CSG) is a geometric modeling technique that defines complex shapes by recursively applying boolean operations on primitives such as spheres and cylinders. We present CSGNet, a deep network architecture that takes as input...

Optimizing Latent Distributions for Non-Adversarial Generative Networks.

IEEE transactions on pattern analysis and machine intelligence
The generator in generative adversarial networks (GANs) is driven by a discriminator to produce high-quality images through an adversarial game. At the same time, the difficulty of reaching a stable generator has been increased. This paper focuses on...

DiCENet: Dimension-Wise Convolutions for Efficient Networks.

IEEE transactions on pattern analysis and machine intelligence
We introduce a novel and generic convolutional unit, DiCE unit, that is built using dimension-wise convolutions and dimension-wise fusion. The dimension-wise convolutions apply light-weight convolutional filtering across each dimension of the input t...

An Efficient Defocus Blur Segmentation Scheme Based on Hybrid LTP and PCNN.

Sensors (Basel, Switzerland)
The defocus or motion effect in images is one of the main reasons for the blurry regions in digital images. It can affect the image artifacts up to some extent. However, there is a need for automatic defocus segmentation to separate blurred and sharp...

Multi-Stream Convolutional Neural Networks for Rotating Machinery Fault Diagnosis under Noise and Trend Items.

Sensors (Basel, Switzerland)
In recent years, rotating machinery fault diagnosis methods based on convolutional neural network have achieved much success. However, in real industrial environments, interfering signals are unavoidable, which may reduce the accuracy of fault diagno...

Deep Prior Approach for Room Impulse Response Reconstruction.

Sensors (Basel, Switzerland)
In this paper, we propose a data-driven approach for the reconstruction of unknown room impulse responses (RIRs) based on the deep prior paradigm. We formulate RIR reconstruction as an inverse problem. More specifically, a convolutional neural networ...

Machine Learning in Injection Molding: An Industry 4.0 Method of Quality Prediction.

Sensors (Basel, Switzerland)
One of the essential requirements of injection molding is to ensure the stable quality of the parts produced. However, numerous processing conditions, which are often interrelated in quite a complex way, make this challenging. Machine learning (ML) a...

XGB-DrugPred: computational prediction of druggable proteins using eXtreme gradient boosting and optimized features set.

Scientific reports
Accurate identification of drug-targets in human body has great significance for designing novel drugs. Compared with traditional experimental methods, prediction of drug-targets via machine learning algorithms has enhanced the attention of many rese...

Intelligent escalator passenger safety management.

Scientific reports
This article addresses an approach to intelligent safety control of passengers on escalators. The aim is to improve the accuracy of detecting threatening situations on escalators in the subway to make decisions to prevent threats and eliminate the co...