We present a deep learning framework that leverages computational homogenization expertise to predict the local stress field and homogenized moduli of heterogeneous materials with two- and three-dimensional periodicity, which is named physics-informed Deep Homogenization Networks (DHN). To this end, the displacement field of a repeating unit cell i...
We present a deep learning framework that leverages computational homogenization expertise to predict the local stress field and homogenized moduli of heterogeneous materials with two- and three-dimensional periodicity, which is named physics-informed Deep Homogenization Networks (DHN). To this end, the displacement field of a repeating unit cell i...
Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning Francisco Lopez-Tiro, Daniel Flores-Araiza, Juan Pablo Betancur-Rengifo, Ivan Reyes-Amezcua, Jacques Hubert, Gilberto Ochoa-Ruiz & Christian Daul Conference paper First Online: 09 November 2023 101 AccessesPart of the Lecture Notes in Computer Science book se...
Deep neural network models have become the dominant approach to a large variety of tasks within music information retrieval (MIR). These models generally require large amounts of (annotated) training data to achieve high accuracy. Because not all applications in MIR have sufficient quantities of training data, it is becoming increasingly common to ...
Published in E3S Web of Conferences
Breast cancer is a major public health issue that may be remedied with early identification and efficient organ therapy. The diagnosis and prognosis of severe and serious illnesses are likely to be followed and examined by a biopsy of the affected organ in order to identify and classify the malignin cells or tissues. The histopathology of tissue is...
It has become mainstream in computer vision and other machine learning domains to reuse backbone networks pre-trained on large datasets as preprocessors. Typically, the last layer is replaced by a shallow learning machine of sorts; the newly-added classification head and (optionally) deeper layers are fine-tuned on a new task. Due to its strong per...
Published in Data in brief
Machining is an essential part of modern manufacturing. During machining, the wear of cutting tools increases, eventually impairing product quality and process stability. Determining when to change a tool to avoid these consequences, while still utilizing most of a tool's lifetime is challenging, as the tool lifetime can vary by more than 100% desp...
Foveated vision is a trait shared by many animals, including humans, but its contribution to visual function compared to species lacking it is still under question. This study suggests that the retinotopic mapping which defines foveated vision may play a critical role in achieving efficient visual performance, notably for image categorisation and l...
This paper discusses the problem of classification when learning on an approximation of the labels. For example, aregression problem can be discretized to obtain a classification problem that is easier to solve. One problem encountered whentraining with the cross-entropy is the overfitting of the features that occurs with coarse labeling. To addres...
