AIMC Topic: Algorithms

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LSO-FastSLAM: A New Algorithm to Improve the Accuracy of Localization and Mapping for Rescue Robots.

Sensors (Basel, Switzerland)
This paper improves the accuracy of a mine robot's positioning and mapping for rapid rescue. Specifically, we improved the FastSLAM algorithm inspired by the lion swarm optimization method. Through the division of labor between different individuals ...

VDBFusion: Flexible and Efficient TSDF Integration of Range Sensor Data.

Sensors (Basel, Switzerland)
Mapping is a crucial task in robotics and a fundamental building block of most mobile systems deployed in the real world. Robots use different environment representations depending on their task and sensor setup. This paper showcases a practical appr...

Vehicle Image Detection Method Using Deep Learning in UAV Video.

Computational intelligence and neuroscience
Traditional machine learning algorithms are susceptible to objective factors such as video quality and weather environment in the vehicle detection of Unmanned Aerial Vehicle (UAV) videos, resulting in poor detection results. A vehicle image detectio...

Learning Enhanced Feature Responses for Visual Object Tracking.

Computational intelligence and neuroscience
Visual object tracking is an important topic in computer vision, which has successfully utilized pretrained convolutional neural networks, such as VGG and ResNet. However, the features extracted by these pretrained models are high dimensional, and th...

Development and validation of a deep learning-based algorithm for colonoscopy quality assessment.

Surgical endoscopy
BACKGROUND: Quality indicators should be assessed and monitored to improve colonoscopy quality in clinical practice. Endoscopists must enter relevant information in the endoscopy reporting system to facilitate data collection, which may be inaccurate...

[Not Available].

Zeitschrift fur medizinische Physik
Spoke trajectory parallel transmit (pTX) excitation in ultra-high field MRI enables B inhomogeneities arising from the shortened RF wavelength in biological tissue to be mitigated. To this end, current RF excitation pulse design algorithms either emp...

Framework for Integrating Equity Into Machine Learning Models: A Case Study.

Chest
Predictive analytic models leveraging machine learning methods increasingly have become vital to health care organizations hoping to improve clinical outcomes and the efficiency of care delivery for all patients. Unfortunately, predictive models coul...

Selection of diagnosis with oncologic relevance information from histopathology free text reports: A machine learning approach.

International journal of medical informatics
Histopathology reports are a primary data source for the case definition phase of a Cancer Registry. By reading the histopathology report, the operator that evaluates an oncology case can define the morphology and topography of cancer, and validate t...

High-Throughput Recognition of Tumor Cells Using Label-Free Elemental Characteristics Based on Interpretable Deep Learning.

Analytical chemistry
With cancer seriously hampering the increasing life expectancy of people, developing an instant diagnostic method has become an urgent objective. In this work, we developed a label-free laser-induced breakdown spectroscopy (LIBS) method for high-thro...