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Jean-Sébastien Dessureault, Félix Clément, Seydou Ba, François Meunier and Daniel Massicotte
The field of interior home design has witnessed a growing utilization of machine learning. However, the subjective nature of aesthetics poses a significant challenge due to its variability among individuals and cultures. This paper proposes an applied ma...
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Leonardo Pinto de Magalhães and Fabrício Rossi
In the cultivation of maize, the leaf area index (LAI) serves as an important metric to determine the development of the plant. Unmanned aerial vehicles (UAVs) that capture RGB images, along with random forest regression (RFR), can be used to indirectly ...
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Feng Cheng, Shuchun Jia and Wei Gao
In order to tackle the issue of carbon emissions in logistics and distribution, a vehicle routing model was proposed with the aim of minimizing the overall cost, which includes the vehicle?s fixed cost, transportation costs, and carbon emission costs. An...
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Ouarda Zedadra, Antonio Guerrieri, Hamid Seridi, Aymen Benzaid and Giancarlo Fortino
Efficiently searching for multiple targets in complex environments with limited perception and computational capabilities is challenging for multiple robots, which can coordinate their actions indirectly through their environment. In this context, swarm ...
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Tingwei Meng, Xiaofang Shan, Zhigang Ren and Qinli Deng
Environmental problems including the depletion of natural resources and energy have drawn a lot of attention from all sectors of society in the context of high-quality global development, and solid waste generated by the construction industry accounts fo...
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Danilo Pau, Andrea Pisani and Antonio Candelieri
In the context of TinyML, many research efforts have been devoted to designing forward topologies to support On-Device Learning. Reaching this target would bring numerous advantages, including reductions in latency and computational complexity, stronger ...
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Usman Javed Butt, Osama Hussien, Krison Hasanaj, Khaled Shaalan, Bilal Hassan and Haider al-Khateeb
As computer networks become increasingly important in various domains, the need for secure and reliable networks becomes more pressing, particularly in the context of blockchain-enabled supply chain networks. One way to ensure network security is by usin...
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Jesse T. Richman and Ryan J. Roberts
Big search data offers the opportunity to identify new and potentially real-time measures and predictors of important political, geographic, social, cultural, economic, and epidemiological phenomena, measures that might serve an important role as leading...
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Liangkun Yu, Xiang Sun, Rana Albelaihi and Chen Yi
Federated learning (FL) is a collaborative machine-learning (ML) framework particularly suited for ML models requiring numerous training samples, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Random Forest, in the co...
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Georgia Papacharalampous, Hristos Tyralis, Anastasios Doulamis and Nikolaos Doulamis
Merging satellite products and ground-based measurements is often required for obtaining precipitation datasets that simultaneously cover large regions with high density and are more accurate than pure satellite precipitation products. Machine and statis...
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