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Found 8 papers, 2 papers with code
Generating Synthetic Multispectral Satellite Imagery from Sentinel-2
Multi-spectral satellite imagery provides valuable data at global scale for many environmental and socio-economic applications.
Semantic Segmentation of Medium-Resolution Satellite Imagery using Conditional Generative Adversarial Networks
The generalization property of CNN is poor for satellite imagery because the data can be very diverse in terms of landscape types, image resolutions, and scarcity of labels for different geographies and seasons.
Localization of Malaria Parasites and White Blood Cells in Thick Blood Smears
This study presents an end-to-end approach for localisation and count of malaria parasites and white blood cells (WBCs) which aid in the effective determination of parasitemia; the quantitative content of parasites in the blood.
Luganda Text-to-Speech Machine
The system was built and trained using locally sourced Luganda language text and audio.
Scoring Root Necrosis in Cassava Using Semantic Segmentation
Cassava a major food crop in many parts of Africa, has majorly been affected by Cassava Brown Streak Disease (CBSD).
Proceedings of the ICLR Workshop on Computer Vision for Agriculture (CV4A) 2020
The workshop was held in conjunction with the International Conference on Learning Representations (ICLR) 2020.
EXPLOITING SEMANTIC COHERENCE TO IMPROVE PREDICTION IN SATELLITE SCENE IMAGE ANALYSIS: APPLICATION TO DISEASE DENSITY ESTIMATION
Our approach utilizes a siamese network to improve the discriminative power of convolutional neural networks on a pair of neighboring scene images.
iCassava 2019 Fine-Grained Visual Categorization Challenge
Viral diseases are major sources of poor yields for cassava, the 2nd largest provider of carbohydrates in Africa. At least 80% of small-holder farmer households in Sub-Saharan Africa grow cassava.
