Identified of Collision Alert in Vehicle Ad hoc based on Machine learning

Jasim, Mohammed S; Zaghden, Nizar; Bouhlel, Med Salim

doi:10.1109/icoco53166.2021.9673495

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…The dataset is improved using salt-pepper noise and Gaussian blurring. This study contributes by outlining the impacts of noise and blurring on SVM classification performance [24].…”

Section: Literature Surveymentioning

confidence: 99%

Automatic image annotation system using deep learning method to analyse ambiguous images

Al-Shammary¹,

Zaghden²,

Bouhlel³

2023

PEN

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“…The dataset is improved using salt-pepper noise and Gaussian blurring. This study contributes by outlining the impacts of noise and blurring on SVM classification performance [24].…”

Section: Literature Surveymentioning

confidence: 99%

Automatic image annotation system using deep learning method to analyse ambiguous images

Al-Shammary¹,

Zaghden²,

Bouhlel³

2023

PEN

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“…Jasim et al in [100] used the K-mean clustering method for collision alerts in school zones for road safety in VANETs. This method collects group messages using parameters like vehicle position, messages and collision type and accident region.…”

Section: ) Machinementioning

confidence: 99%

Position-Based Emergency Message Dissemination Schemes in the Internet of Vehicles: A Review

Ahmed,

Iqbal,

Jabbar

et al. 2023

IEEE Trans. Intell. Transport. Syst.

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“…As a result, the semantic analysis focuses on the characteristics of video and their related characteristics, which include colors, edges, and arcs… etc. [3]. There are three levels of semantic analysis, (1) low-level semantic analysis techniques focus on the capacity to identify the visual areas that correspond to items of interest (detection), follow those objects over many frames, and keep their identities (tracking), (2) Simple or "atomic" actions or behaviors including loitering, falls, direction changes, group forms, and separations might be difficult for mid-level semantic analysis tools to identify.…”

Section: Introductionmentioning

confidence: 99%

Road conditions monitoring using semantic segmentation of smartphone motion sensor data

Mahmood,

Zaghden,

Mejdoub

2023

PEN

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Many studies and publications have been written about the use of moving object analysis to locate a specific item or replace a lost object in video sequences. Using semantic analysis, it could be challenging to pinpoint each meaning and follow the movement of moving objects. Some machine learning algorithms have turned to the right interpretation of photos or video recordings to communicate coherently. The technique converts visual patterns and features into visual language using dense and sparse optical flow algorithms. To semantically partition smartphone motion sensor data for any video categorization, using integrated bidirectional Long Short-Term Memory layers, this paper proposes a redesigned U-Net architecture. Experiments show that the proposed technique outperforms several existing semantic segmentation algorithms using z-axis accelerometer and z-axis gyroscope properties. The video sequence's numerous moving elements are synchronised with one another to follow the scenario. Also, the objective of this work is to assess the proposed model on roadways and other moving objects using five datasets (self-made dataset and the pothole600 dataset). After looking at the map or tracking an object, the results should be given together with the diagnosis of the moving object and its synchronization with video clips. The suggested model's goals were developed using a machine learning method that combines the validity of the results with the precision of finding the necessary moving parts. Python 3.7 platforms were used to complete the project since they are user-friendly and highly efficient platforms.

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Identified of Collision Alert in Vehicle Ad hoc based on Machine learning

Cited by 5 publications

References 24 publications

Automatic image annotation system using deep learning method to analyse ambiguous images

Automatic image annotation system using deep learning method to analyse ambiguous images

Position-Based Emergency Message Dissemination Schemes in the Internet of Vehicles: A Review

Road conditions monitoring using semantic segmentation of smartphone motion sensor data

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