Andere Kunden interessierten sich auch für
![PREDICTION OF CROP YIELD USING DEEP LEARNING]( "PREDICTION OF CROP YIELD USING DEEP LEARNING")
PREDICTION OF CROP YIELD USING DEEP LEARNING29,99 €![A Screening and Identification Study on GM Tomatoes and Tomato Seeds]( "A Screening and Identification Study on GM Tomatoes and Tomato Seeds")
A Screening and Identification Study on GM Tomatoes and Tomato Seeds38,99 €![Crop Yield Prediction at various Districts of Karnataka using ML]( "Crop Yield Prediction at various Districts of Karnataka using ML")
Crop Yield Prediction at various Districts of Karnataka using ML29,99 €![Primate Seed Dispersal, Seed Germination and Tree Regeneration]( "Primate Seed Dispersal, Seed Germination and Tree Regeneration")
Primate Seed Dispersal, Seed Germination and Tree Regeneration32,99 €![Vorhersage der Keimung von Tomatensamen aus Bildern mit Deep Learning]( "Vorhersage der Keimung von Tomatensamen aus Bildern mit Deep Learning")
Vorhersage der Keimung von Tomatensamen aus Bildern mit Deep Learning43,90 €![Multivariate Statistical Machine Learning Methods for Genomic Prediction]( "Multivariate Statistical Machine Learning Methods for Genomic Prediction")
Multivariate Statistical Machine Learning Methods for Genomic Prediction30,99 €![Multivariate Statistical Machine Learning Methods for Genomic Prediction]( "Multivariate Statistical Machine Learning Methods for Genomic Prediction")
Multivariate Statistical Machine Learning Methods for Genomic Prediction37,99 €
This book is related to the application of deep learning in agricultural field. In fact, researches were carried out to predict the tomato seeds germinability from images with deep learning under proper growing conditions. This task was a classification task which was tricky as the classes were imbalance. To assess the models, macro f1 score was used.In the analysis, a baseline model was used which consisted of three convolutional layers and then the classification layer after a flattening operation.Some useful pre-trained models such VGG-19, ResNet-50, were also used in order to leverage the new task.Even though the classification was so difficult, the above techniques were so useful in achieving 0.52 which is better than humain guessing skills.