A variant of DBSCAN algorithm to find embedded and nested adjacent clusters

Nagaraju, Samudrala; Kashyap, Manish; Bhattacharya, Mahua

doi:10.1109/spin.2016.7566744

Cited by 8 publications

(2 citation statements)

References 12 publications

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“…Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is popular and, as the name suggests, a ‘density-based clustering non-parametric algorithm’ [ 39 ]. If a set of points are fed to its input, the algorithm works towards grouping points that are closely packed [ 40 ]. The algorithm marks such points as ‘inliers’.…”

Section: Proposed Fusion Methodsmentioning

confidence: 99%

Centralised and Decentralised Sensor Fusion-Based Emergency Brake Assist

Deo¹,

Palade

Huda

2021

Sensors

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Many advanced driver assistance systems (ADAS) are currently trying to utilise multi-sensor architectures, where the driver assistance algorithm receives data from a multitude of sensors. As mono-sensor systems cannot provide reliable and consistent readings under all circumstances because of errors and other limitations, fusing data from multiple sensors ensures that the environmental parameters are perceived correctly and reliably for most scenarios, thereby substantially improving the reliability of the multi-sensor-based automotive systems. This paper first highlights the significance of efficiently fusing data from multiple sensors in ADAS features. An emergency brake assist (EBA) system is showcased using multiple sensors, namely, a light detection and ranging (LiDAR) sensor and camera. The architectures of the proposed ‘centralised’ and ‘decentralised’ sensor fusion approaches for EBA are discussed along with their constituents, i.e., the detection algorithms, the fusion algorithm, and the tracking algorithm. The centralised and decentralised architectures are built and analytically compared, and the performance of these two fusion architectures for EBA are evaluated in terms of speed of execution, accuracy, and computational cost. While both fusion methods are seen to drive the EBA application at an acceptable frame rate (~20fps or higher) on an Intel i5-based Ubuntu system, it was concluded through the experiments and analytical comparisons that the decentralised fusion-driven EBA leads to higher accuracy; however, it has the downside of a higher computational cost. The centralised fusion-driven EBA yields comparatively less accurate results, but with the benefits of a higher frame rate and lesser computational cost.

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Section: Proposed Fusion Methodsmentioning

confidence: 99%

Centralised and Decentralised Sensor Fusion-Based Emergency Brake Assist

Deo¹,

Palade

Huda

2021

Sensors

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“…Based on neighbourhood difference and density based notion of clusters, Nagaraju et al [71] proposed an improved version of DBSCAN for detecting embedded and nested adjacent clusters. Results of experiments showed that the proposed work outperforms when compared to DBSCAN.…”

Section: Clusteringmentioning

confidence: 99%

An Overview on User Profiling in Online Social Networks

Vasanthakumar¹,

Sunithamma²,

Shenoy³

et al. 2017

IJAIS

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Advances in Online Social Networks is creating huge data day in and out providing lot of opportunities to its users to express their interest and opinion. Due to the popularity and exposure of social networks, many intruders are using this platform for illegal purposes. Identifying such users is challenging and requires digging huge knowledge out of the data being flown in the social media. This work gives an insight to profile users in online social networks. User Profiles are established based on the behavioral patterns, correlations and activities of the user analyzed from the aggregated data using techniques like clustering, behavioral analysis, content analysis and face detection. Depending on application and purpose, the mechanism used in profiling users varies. Further study on other mechanisms used in profiling users is under the scope of future endeavors.

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Accurate extraction method of multi-laser stripes for stereo-vision based handheld scanners in complex circumstances

Yang,

Zhang

et al. 2025

Optics & Laser Technology

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A variant of DBSCAN algorithm to find embedded and nested adjacent clusters

Cited by 8 publications

References 12 publications

Centralised and Decentralised Sensor Fusion-Based Emergency Brake Assist

Centralised and Decentralised Sensor Fusion-Based Emergency Brake Assist

An Overview on User Profiling in Online Social Networks

Accurate extraction method of multi-laser stripes for stereo-vision based handheld scanners in complex circumstances

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