Integrating Line Transect Distance Sampling and Spatial Analysis to Assess Local Density and Habitat Use of Capra aegagrus in Batman Province, Türkiye [PDF]
LifeUnderstanding local population density and spatial habitat use is essential for wildlife conservation in fragmented mountainous landscapes. This study examined the habitat use patterns of Capra aegagrus in the mountainous regions of Batman, Türkiye ...
Eyüp Yıldırım, Servet Ulutürk
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VESPER: global and local cryo-EM map alignment using local density vectors [PDF]
Nature Communications, 2021 Here, the authors present VESPER, a program for EM density map search and alignment. Using benchmark datasets, they demonstrate that VESPER performs accurate global and local alignments and comparisons of EM maps.
Xusi Han +4 more
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Research on Ground Point Cloud Segmentation Algorithm Based on Local Density Plane Fitting in Road Scene [PDF]
SensorsIn road scenes, the collected 3D point cloud data is usually accompanied by a large amount of interference mainly composed of ground point clouds and the property of uneven density distribution, which will bring difficulties to subsequent recognition and
Tao Wang +7 more
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UAV Sensor Fault Detection Using a Classifier without Negative Samples: A Local Density Regulated Optimization Algorithm [PDF]
Sensors, 2019 Fault detection for sensors of unmanned aerial vehicles is essential for ensuring flight security, in which the flight control system conducts real-time control for the vehicles relying on the sensing information from sensors, and erroneous sensor data ...
Kai Guo +4 more
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Model-based local density sharpening of cryo-EM maps [PDF]
eLife, 2017 Atomic models based on high-resolution density maps are the ultimate result of the cryo-EM structure determination process. Here, we introduce a general procedure for local sharpening of cryo-EM density maps based on prior knowledge of an atomic ...
Arjen J Jakobi +2 more
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Generative adversarial local density-based unsupervised anomaly detection. [PDF]
PLoS ONEAnomaly detection is crucial in areas such as financial fraud identification, cybersecurity defense, and health monitoring, as it directly affects the accuracy and security of decision-making.
Xinliang Li +4 more
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Tri-Training Algorithm for Adaptive Nearest Neighbor Density Editing and Cross Entropy Evaluation
Entropy, 2023 Tri-training expands the training set by adding pseudo-labels to unlabeled data, which effectively improves the generalization ability of the classifier, but it is easy to mislabel unlabeled data into training noise, which damages the learning efficiency
Jia Zhao +4 more
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Density Peak Clustering Algorithm Based on Shared Neighborhood
Journal of Harbin University of Science and Technology, 2023 To solve the problem of poor clustering performance and automatic determination of cluster center inthe processing of unevenly distributed datasets, a density peak clustering algorithm based on shared neighborhood is proposed ( DPC-SN) .
LI Fuxiang, ZHOU Ming, YANG Tianhao
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Co-Density Distribution Maps for Advanced Molecule Colocalization and Co-Distribution Analysis
Sensors, 2021 Cellular and subcellular spatial colocalization of structures and molecules in biological specimens is an important indicator of their co-compartmentalization and interaction.
Ilaria De Santis +6 more
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F-DPC: Fuzzy Neighborhood-Based Density Peak Algorithm
IEEE Access, 2020 Clustering is a concept in data mining, which divides a data set into different classes or clusters according to a specific standard, making the similarity of data objects in the same cluster as large as possible.
Yang Li, Wenju Zhou, Haikuan Wang
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