Results 11 to 20 of about 170,348 (267)
A Fusion-Based Defogging Algorithm [PDF]
Remote Sensing, 2022 To solve the problem that traditional dark channel is not suitable for a large sky area and can easyily distort defogged images, we propose a novel fusion-based defogging algorithm. Firstly, an improved remote sensing image segmentation algorithm is introduced to mix the dark channel.
Ting Chen 0003 +5 more
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The fusion–fission optimization (FuFiO) algorithm
Scientific Reports, 2022 AbstractFusion–Fission Optimization (FuFiO) is proposed as a new metaheuristic algorithm that simulates the tendency of nuclei to increase their binding energy and achieve higher levels of stability. In this algorithm, nuclei are divided into two groups, namely stable and unstable. Each nucleus can interact with other nuclei using three different types
Behnaz Nouhi +5 more
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THE S2-ENSEMBLE FUSION ALGORITHM [PDF]
International Journal of Neural Systems, 2011 This paper presents a novel model for performing classification and visualization of high-dimensional data by means of combining two enhancing techniques. The first is a semi-supervised learning, an extension of the supervised learning used to incorporate unlabeled information to the learning process.
Bruno Baruque +2 more
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TopHat-Fusion: an algorithm for discovery of novel fusion transcripts [PDF]
Genome Biology, 2011 AbstractTopHat-Fusion is an algorithm designed to discover transcripts representing fusion gene products, which result from the breakage and re-joining of two different chromosomes, or from rearrangements within a chromosome. TopHat-Fusion is an enhanced version of TopHat, an efficient program that aligns RNA-seq reads without relying on existing ...
Kim, Daehwan, Salzberg, Steven L
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A Risk Profile for Information Fusion Algorithms [PDF]
Entropy, 2011 E.T. Jaynes, originator of the maximum entropy interpretation of statistical mechanics, emphasized that there is an inevitable trade-off between the conflicting requirements of robustness and accuracy for any inferencing algorithm. This is because robustness requires discarding of information in order to reduce the sensitivity to outliers.
Kenric P. Nelson +2 more
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A comparison of track-to-track fusion algorithms for automotive sensor fusion [PDF]
2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2008 In exteroceptive automotive sensor fusion, sensor data are usually only available as processed, tracked object data and not as raw sensor data. Applying a Kalman filter to such data leads to additional delays and generally underestimates the fused objectspsila covariance due to temporal correlations of individual sensor data as well as inter-sensor ...
Stephan Matzka, Richard Altendorfer
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Symptom Analysis Using Fuzzy Logic for Detection and Monitoring of COVID-19 Patients
Energies, 2021 Recent developments regarding the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) opened new horizons of healthcare opportunities.
Tayyaba Ilyas +3 more
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Underground personnel positioning system based on fingerprint and dead-reckoning
Gong-kuang zidonghua, 2016 In view of problem that RSSI-based fingerprint positioning method is greatly influenced by environment of coal mine tunnel, and localization method based on dead-reckoning is easy to form accumulation of errors, underground personnel positioning system ...
MA Jing +3 more
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A Review of Depth and Normal Fusion Algorithms [PDF]
Sensors, 2018 Geometric surface information such as depth maps and surface normals can be acquired by various methods such as stereo light fields, shape from shading and photometric stereo techniques. We compare several algorithms which deal with the combination of depth with surface normal information in order to reconstruct a refined depth map.
Doris Antensteiner +2 more
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Research on the Path Planning of Unmanned Sweepers Based on a Fusion Algorithm
Applied Sciences, 2023 Path planning is one of the key technologies for unmanned driving. However, global paths are unable to avoid unknown obstacles, while local paths tend to fall into local optimality.
Yongjie Ma, Peng Ping, Quan Shi
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