quantumT Computer Vision Project

TLCM

Updated a year ago

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Classes (16)
1B-1L
1B-1L-F
1B-2L
1B-2L-F
1B-3L
1B-3L-F
1B-4F
coarse
double-banjhi
double-banjhi-1L
double-banjhi-2L
double-banjhi-F
fine
other
touching
unsure
Description

Here are a few use cases for this project:

  1. Agricultural Analysis: This QuantumT can be very beneficial for farmers and agriculture experts. By classifying different types of plants, weeds, and plant diseases based on leaf conditions, the system could provide guidance on necessary treatments or interventions.

  2. Botanical Research: Scientists can use QuantumT to identify and study different types of plants and leaf conditions. The system can sort through thousands of leaf samples quickly, allowing researchers to focus on analysis and making scientific breakthroughs.

  3. Smart Gardening Apps: QuantumT can be built into a gardening app that helps users identify and care for different kinds of plants in their garden. Users can simply take pictures of their plants and the app would tell them what type of plant it is and how to care for it.

  4. Environmental Impact Studies: QuantumT can help environmentalists understand the impact of various factors on vegetation. This can include tracking the spread of plant diseases, the impact of pollution on vegetation, and the effects of climate change on different plant classes.

  5. Biodiversity Monitoring: Conservation biologists can use QuantumT for tracking biodiversity in specific areas by identifying and cataloging plant species based on leaf images. This can help in maintaining the balance of ecosystems and in making essential conservation decisions.

Supervision

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Cite This Project

LICENSE
MIT

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

                        @misc{
                            quantumt_dataset,
                            title = { quantumT Dataset },
                            type = { Open Source Dataset },
                            author = { TLCM },
                            howpublished = { \url{ https://universe.roboflow.com/tlcm/quantumt } },
                            url = { https://universe.roboflow.com/tlcm/quantumt },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-11-14 },
                            }
                        
                    

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