kmutnb_person_com Computer Vision Project

Prod Seyes

Updated 2 years ago

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Classes (2)
com_on
person

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Description

Here are a few use cases for this project:

  1. Classroom Attendance Management: "kmutnb_person_com" can be used in educational institutions to monitor and track student attendance by analyzing images or video feeds from classrooms, identifying the presence of students (person class) and checking them against the registered list of students in the class.

  2. Workspace Productivity Analysis: Businesses can utilize this model to analyze office spaces and monitor employee activities. By identifying individuals (person class) and their interaction with computers (com_on), companies can better understand and optimize employee productivity.

  3. Smart Building Management: The computer vision model can be integrated into smart building systems to detect and monitor the occupancy of shared spaces such as conference rooms, study areas, or libraries. The model can identify the presence of people and their activities, providing building managers information on space utilization and energy consumption.

  4. Retail Space Analysis: Retailers can use "kmutnb_person_com" to analyze and improve their store layouts. By detecting the presence of customers (person class) and their activities near products or computers (com_on), retailers can optimize the arrangement of merchandise and digital displays to increase customer engagement and sales.

  5. Security and Surveillance: The computer vision model could be implemented in security systems to monitor and detect unauthorized access to sensitive areas where computers or critical infrastructure are present. By detecting the presence of individuals (person class), security personnel can quickly respond to potential threats.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            kmutnb_person_com_dataset,
                            title = { kmutnb_person_com Dataset },
                            type = { Open Source Dataset },
                            author = { Prod Seyes },
                            howpublished = { \url{ https://universe.roboflow.com/prod-seyes/kmutnb_person_com } },
                            url = { https://universe.roboflow.com/prod-seyes/kmutnb_person_com },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

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