Optimal Selection of Data Augmentation Transformations

To achieve useful results in training deep neural network, one typically needs huge number of labelled images. In most practical cases, it is often time consuming, expensive and sometimes even near impossible to get the required numbers of labelled images. Data augmentation consists in a set of image processing techniques that can be applied to […]

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Conversion of lignocellulosic biomass or waste materials into value-added products via hydrothermal fractionation and liquefaction/gasification

I propose the study on intermediate (value-added) product production from distributed lignocellulosic biomass or waste materials through hydrothermal fractionation/liquefaction/gasification. In future, supply-chain network system is important because of reduction of electric loss. It can avoid food and unused land use issues. also, biofuels are considered carbon-neutral as the plant recycle the CO2 released from their […]

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Design of a real-time on-site biosensor system to monitor harmful pathogens and protect canola production

Canada is one of the largest canola producing countries. The industry contributes about $20 billion revenue to the Canadian economy. Currently, canola farmers rely on the weather forecast (temperature, moisture, etc.) to decide whether to apply a fungicide. As the Internet-of-Things and sensor technologies get more advanced, farmers are deserved to have better technologies for […]

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The Net Effect of Technical Non-Tariff Measures in OCDE countries on African Exports of Vegetable products

Durant les trente dernières années, l’utilisation des mesures non tarifaires (MNT) des chapitres A (SPS) et B (OTC) s’est accrue dans les pays développés. Elles représentaient 59% des MNT en 2012 (WTO 2012) et 70% en 2017 (UNCTAD, 2017). Ces mesures techniques traitent diverses préoccupations (qualité et sécurité sanitaire) liées à la production et aux […]

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Decoding communication profiles of AMF-soil microbiota with cannabis for higher yield and environmental safety

Chemical fertilizers and pesticides are extensively used for commercial growth of cannabis alike other crops. More than 40% of unused fertilizers cause serious environmental problems such as contaminants transform into our food chain, and eventually repeated application of chemical fertilizers increase human and ecosystem (human health, floral and faunal diversity) health risks over the time. […]

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Applying Machine Learning to Predict Demand Transference

The project will help us design a machine learning model that can determine the demand transference of our customers. The key objective of this project is to design, research, build, and experiment with machine learning models to ensure low product waste and high customer satisfaction. The model will have several impactful applications across the organization.

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Contrôle qualité et détection de défauts pour des systèmes d’ensachage industriel par l’utilisation du Deep Learning

L’opération d’emballage dans des sacs flexibles de produits en vrac est utilisée au quotidien par l’industrie agroalimentaire. Cependant, un défaut de fermeture d’un des sacs présents sur une palette entraine la perte de toute la palette pour garantir les normes d’hygiènes. Le but du projet est de proposer une solution qui permet de détecter les […]

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Auto-configuration of an autonomous farming vehicle using Machine Learning

Precision agriculture has many benefits especially for the developing world. Autonomous tractors and automatic planting systems have high accuracy, resulting in a substantially improved return on investment for growers, making food planting more economical. Moreover, the tractors can collect information on soil conditions, which can lead to improved maintenance of the crops, prevent blights, and […]

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