AIMC Topic: Algorithms

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Semi-Supervised Anomaly Detection in Video-Surveillance Scenes in the Wild.

Sensors (Basel, Switzerland)
Surveillance cameras are being installed in many primary daily living places to maintain public safety. In this video-surveillance context, anomalies occur only for a very short time, and very occasionally. Hence, manual monitoring of such anomalies ...

Camera-LiDAR Multi-Level Sensor Fusion for Target Detection at the Network Edge.

Sensors (Basel, Switzerland)
There have been significant advances regarding target detection in the autonomous vehicle context. To develop more robust systems that can overcome weather hazards as well as sensor problems, the sensor fusion approach is taking the lead in this cont...

Soft-Sensor for Class Prediction of the Percentage of Pentanes in Butane at a Debutanizer Column.

Sensors (Basel, Switzerland)
Refineries are complex industrial systems that transform crude oil into more valuable subproducts. Due to the advances in sensors, easily measurable variables are continuously monitored and several data-driven soft-sensors are proposed to control the...

Benefits of deep learning classification of continuous noninvasive brain-computer interface control.

Journal of neural engineering
. Noninvasive brain-computer interfaces (BCIs) assist paralyzed patients by providing access to the world without requiring surgical intervention. Prior work has suggested that EEG motor imagery based BCI can benefit from increased decoding accuracy ...

Diagnosis of Chronic Kidney Disease Using Effective Classification Algorithms and Recursive Feature Elimination Techniques.

Journal of healthcare engineering
Chronic kidney disease (CKD) is among the top 20 causes of death worldwide and affects approximately 10% of the world adult population. CKD is a disorder that disrupts normal kidney function. Due to the increasing number of people with CKD, effective...

A machine learning approach to predicting risk of myelodysplastic syndrome.

Leukemia research
BACKGROUND: Early myelodysplastic syndrome (MDS) diagnosis can allow physicians to provide early treatment, which may delay advancement of MDS and improve quality of life. However, MDS often goes unrecognized and is difficult to distinguish from othe...

Deep probabilistic tracking of particles in fluorescence microscopy images.

Medical image analysis
Tracking of particles in temporal fluorescence microscopy image sequences is of fundamental importance to quantify dynamic processes of intracellular structures as well as virus structures. We introduce a probabilistic deep learning approach for fluo...

Non-line-of-Sight Imaging via Neural Transient Fields.

IEEE transactions on pattern analysis and machine intelligence
We present a neural modeling framework for non-line-of-sight (NLOS) imaging. Previous solutions have sought to explicitly recover the 3D geometry (e.g., as point clouds) or voxel density (e.g., within a pre-defined volume) of the hidden scene. In con...

BlockQNN: Efficient Block-Wise Neural Network Architecture Generation.

IEEE transactions on pattern analysis and machine intelligence
Convolutional neural networks have gained a remarkable success in computer vision. However, most popular network architectures are hand-crafted and usually require expertise and elaborate design. In this paper, we provide a block-wise network generat...

GHOST: Adjusting the Decision Threshold to Handle Imbalanced Data in Machine Learning.

Journal of chemical information and modeling
Machine learning classifiers trained on class imbalanced data are prone to overpredict the majority class. This leads to a larger misclassification rate for the minority class, which in many real-world applications is the class of interest. For binar...