Pollen Grain Classification Using Some Convolutional Neural Network Architectures.

The main objective of this work is to use convolutional neural networks (CNN) to improve the performance in previous works on their baseline for pollen grain classification, by improving the performance of the following eight popular architectures: InceptionV3, VGG16, VGG19, ResNet50, NASNet, Xception, DenseNet201 and InceptionResNetV2, which are benchmarks on several classification tasks, like on the ImageNet dataset. We use a well-known annotated public image dataset for the Brazilian savanna, called POLLEN73S, composed of 2523 images. Holdout cross-validation is the name of the method used in this work.

Classification of Pepper Seeds by Machine Learning Using Color Filter Array Images.

The purpose of this work is to classify pepper seeds using color filter array (CFA) images. This study focused specifically on Penja pepper, which is found in the Litoral region of Cameroon and is a type of . India and Brazil are the largest producers of this variety of pepper, although the production of Penja pepper is not as significant in terms of quantity compared to other major producers.

Mathematical modeling, analysis and numerical simulation of the transmission with mitigation of control strategies used in Cameroon.

In this paper, we formulated a general model of model transmission using biological features of the disease and control strategies based on the isolation of exposed people, confinement (lock-downs) of the human population, testing people living risks area, wearing of masks and respect of hygienic rules. We provide a theoretical study of the model. We derive the basic reproduction number which determines the extinction and the persistence of the infection.

Forecasting of COVID-19 pandemic: From integer derivatives to fractional derivatives.

In this work, a new compartmental mathematical model of COVID-19 pandemic has been proposed incorporating imperfect quarantine and disrespectful behavior of citizens towards lockdown policies, which are evident in most of the developing countries. An integer derivative model has been proposed initially and then the formula for calculating basic reproductive number, of the model has been presented. Cameroon has been considered as a representative for the developing countries and the epidemic threshold, has been estimated to be  ~ 3.

Bifurcation thresholds and optimal control in transmission dynamics of arboviral diseases.

In this paper, we derive and analyse a model for the control of arboviral diseases which takes into account an imperfect vaccine combined with some other control measures already studied in the literature. We begin by analysing the basic model without control. We prove the existence of two disease-free equilibrium points and the possible existence of up to two endemic equilibrium points (where the disease persists in the population).

Backward bifurcation and control in transmission dynamics of arboviral diseases.

In this paper, we derive and analyze a compartmental model for the control of arboviral diseases which takes into account an imperfect vaccine combined with individual protection and some vector control strategies already studied in the literature. After the formulation of the model, a qualitative study based on stability analysis and bifurcation theory reveals that the phenomenon of backward bifurcation may occur. The stable disease-free equilibrium of the model coexists with a stable endemic equilibrium when the reproduction number, R0, is less than unity.