Maize Seed Dataset

Datasets

Maize Seed

File

Maize Seed

Use Case

Maize Seed

Description

Explore our comprehensive Maize Seed featuring 17,724 hyperspectral images across three local Ghanaian varieties.

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Description:

This dataset focuses on the classification of maize seeds using advanced deep learning techniques in conjunction with hyperspectral imaging. The primary objective is to overcome the challenges associated with deploying these computationally intensive methods on embedded devices, particularly due to the high power consumption of GPUs. By addressing these challenges, the goal is to develop an efficient, cost-effective maize classification tool that minimizes the need for human intervention. Hyperspectral imaging provides a powerful means of capturing detailed spectral information across a wide range of wavelengths, which is crucial for distinguishing between different maize varieties with high accuracy. This technology, when combined with deep learning algorithms, can significantly enhance the precision of maize seed classification.

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Content:

Total Entries: 17,724 images
Classes:
- Bhihilifa: 6,480 images
- Sanzal Sima: 5,100 images
- Wang Dataa: 6,144 images

Purpose: The development of automated maize seed grading systems is essential for enhancing the efficiency and effectiveness of maize production and marketing in Ghana. Local Ghanaian maize varieties have unique characteristics that need to be considered when designing these systems. By implementing automated grading, we aim to improve the quality control, reduce labor costs, and increase the competitiveness of Ghanaian maize in the market.