Author: Lorenzo Brigato

Lorenzo Brigato is a Postdoctoral Researcher at the ARTORG center, a research institution affiliated with the University of Bern, and is currently involved in the application of AI to health and nutrition. He holds a Ph.D. degree in Computer Science from the Sapienza University of Rome, Italy. His Ph.D. thesis focused on image classification problems with sample- and label-deficient data distributions.
JupyterLab is fundamentally intended to be an extendable environment. Any component of JupyterLab can be enhanced or customized using JupyterLab extensions. New themes, file viewers and editors, or renderers enabling rich outputs in notebooks are some...
It has never been simpler to capture a realistic digital representation of a real-world 3D scene, thanks to the development of effective neural 3D reconstruction techniques. The steps are straightforward: Take several pictures of a scene from...

Vision Transformers Have Taken The Field of Computer Vision by Storm, But What Do Vision Transformers Learn?

Vision transformers (ViTs) are a type of neural network architecture that has reached tremendous popularity for vision tasks such as image classification, semantic segmentation,...

A New Paradigm For Editing Machine Learning Models Based on Arithmetic Operations Over Task Vectors

It is becoming increasingly common to use large-scale pre-training to develop models employed as the foundation for more specialized machine learning systems. From a...

Westlake University Researchers Propose ‘SimVP,’ An Artificial Intelligence AI-Based Video Prediction Model that is Completely Built Upon CNN and Trained by MSE Loss in...

Video prediction is a challenging yet critical task that is required to enable intelligent machines to foresee the future and eventually better act in...

Comprehensive Overview and Dedicated Benchmark for Deep Learning from Small Datasets in the Context of Image Classification

Many recent advances in computer vision and machine learning, in general, have been achieved by large-scale pre-training on massive datasets. However, reaching high recognition...

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