Applying Machine Learning and Data Fusion to the “Missing Person” Problem

Solaiman, K. M. A.; Sun, Tao; Nesen, Alina; Bhargava, Bharat

doi:10.1109/mc.2022.3145507

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…In the process of controlling water pollution, it is mainly realized by monitoring and controlling environmental factors (pollutants, water quality, etc, These conditions will affect the effect of water pollution prevention, so instruments and equipment must be used to measure the sewage composition and pollutant concentration [9][10]. In the process of controlling water pollution, we need to treat environmental pollutants according to the actual situation.…”

Section: Water Pollution Preventionmentioning

confidence: 99%

Model Construction of Water Pollution Prevention Project Based on Small Sample Learning and Data Fusion

2023

WPPCP

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At present, the problem of water pollution in China is becoming more and more serious. In view of the scarcity of water resources and deterioration of environmental quality, it is necessary to effectively control pollutants in water bodies. This paper mainly studies the causes of pollutants in small sample data through learning and experiment methods, and takes them as the precondition to connect with the actual environment. On this basis, the improvement measures based on indoor water pollution monitoring and prediction are constructed to analyze, sort out and model the above problems. The emission concentration distribution map obtained by MATLAB software combined with laboratory simulation is used to verify that the above theoretical model is feasible and effective to solve the harmful problems caused by water quality deterioration. The test results show that, based on small sample learning and data fusion technology, It has a certain effect on the water pollution prevention project and can monitor the water pollution.

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Section: Water Pollution Preventionmentioning

confidence: 99%

Model Construction of Water Pollution Prevention Project Based on Small Sample Learning and Data Fusion

2023

WPPCP

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“…Deep learning has been successfully applied to a variety of fields, including computer vision and machine vision (Gholape et al, 2021;Solaiman et al, 2022;Kundid Vasić and Papić, 2020). Face recognition techniques are particularly useful for searching for missing people, as they save time and effort.…”

Section: Introductionmentioning

confidence: 99%

Suhail: A Deep Learning-Based System for Identifying Missing People

Aljohani¹,

Alshehri²,

Alghamdi³

et al. 2023

CIS

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Many people become missing in Saudi Arabia every day, including children, young people, and the mentally ill as well as the elderly with Alzheimer’s. There are many missing people cases that are still unsolved. In Saudi Arabia, people use social media platforms such as Twitter to report missing people cases. The application of deep learning has been successful in a wide range of fields including computer vision and machine vision. In particular, face recognition techniques are effective in saving time and effort, especially when searching for missing individuals. Hence, the goal of this research is to solve this issue by developing a deep learning-based system for identifying missing individuals. This paper introduces a new system called Suhail. The system has been implemented and developed using Android Studio and open-source libraries such as TensorFlow. First, users or governments can report missing persons by uploading photos. Updates and information will then be shared with the rest of the system’s users (volunteers). Once a volunteer discovers a suspect, they scan their face using camera. Then, our application uses face recognition techniques to compare the suspect's photo with photos from the repository. Finally, once a comparison is found, our application contacts the suspect’s family, informs them of his location and then notifies the police that a missing person has been located. By using our application and face recognition systems, we help families and police locate and reach a missing person which saves time and effort. In this study, 759 participants were enrolled to evaluate the performance of the Suhail system. Engagement, aesthetics, and functionality are used to evaluate the user experience. The results of the experiment show that users enjoy the new features of the application and that the system is simple to use. Moreover, the system would help governments and individuals identify missing people faster.

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A Web Portal for Tracking and Finding Missing Person Using Aadhaar Enabled Biometrics

2024

JITDW

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The Aadhaar-Enabled Biometric Web Portal for Finding Missing Persons research aims to address the critical issue of locating missing individuals by leveraging Aadhaar-enabled biometric data. With the widespread adoption of Aadhaar cards in India, this research uses the unique biometric information linked to Aadhaar cards to create a web portal. Through this portal, users can input relevant biometric data, such as fingerprints or iris scans, which are then compared with the Aadhaar database. The system utilizes advanced biometric matching algorithms to accurately identify potential matches, thereby aiding law enforcement agencies and concerned individuals in locating missing persons efficiently. By integrating Aadhaar-enabled biometrics into a user-friendly web interface, this research facilitates swift and accurate identification, offering a valuable tool in the effort to reunite missing individuals with their families and loved ones.

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Applying Machine Learning and Data Fusion to the “Missing Person” Problem

Abstract: We present a system for integrating multiple sources of data for finding missing persons. It can help authorities find children, developmentally challenged individuals who have wandered off, and persons of interest in investigations.

Cited by 3 publications

References 16 publications

Model Construction of Water Pollution Prevention Project Based on Small Sample Learning and Data Fusion

Model Construction of Water Pollution Prevention Project Based on Small Sample Learning and Data Fusion

Suhail: A Deep Learning-Based System for Identifying Missing People

A Web Portal for Tracking and Finding Missing Person Using Aadhaar Enabled Biometrics

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