[EN] The increasing demand for efficient and safe transportation systems has led to the development of autonomous vehicles and vehicle platooning. Truck platooning, in particular, offers numerous benefits, such as reduced ...

[EN] This paper sets forth a methodology that is based on three-stage-training of a state-of-the-art network architecture previously trained on Imagenet, and iteratively finetuned in three steps; freezing first all layers, ...

[ES] El advenimiento de los Large Language Models (LLMs) marca una fase transformadora en el campo de la Inteligencia Artificial (IA), significando el cambio hacia sistemas inteligentes y autónomos capaces de una comprensión ...

[EN] With the rise in traffic congestion in urban centers, predicting accidents has become paramount for city planning and public safety. This work comprehensively studied the efficacy of modern deep learning (DL) methods ...

[EN] The library explores the applicability of the Hadamard as an input modulator for problems of classification. It introduces a framework in C++ to use kernel approximates in the mini-batch setting with Stochastic Gradient ...

[EN] Imbalanced datasets pose pervasive challenges in numerous machine learning (ML) applications, notably in areas such as fraud detection, where fraudulent cases are vastly outnumbered by legitimate transactions. ...

[EN] This manuscript presents a new benchmark for assessing the quality of visual summaries without the need for human annotators. It is based on the Signature Transform, specifically focusing on the RMSE and the MAE ...