SQL & NOSQL Data Management Systems Permalink
๐ Modelling and querying of a countries-states-cities dataset with SQL (Postgresql) and NOSQL (Neo4j) approaches. Optimization of SQL and NOSQL queries to reduce the execution time.
๐ Modelling and querying of a countries-states-cities dataset with SQL (Postgresql) and NOSQL (Neo4j) approaches. Optimization of SQL and NOSQL queries to reduce the execution time.
โจ๏ธ Reimplementation of Top Linux shell command.
๐น Implementation of DQfD tested on Pong Gym environment and Montezuma Revenge Gym environment (the latter with sparse reward).
๐ฅ This web app allows the rapid inizialitazion of projects on GitLab through a very simple user interface. By filling in the required fields, the project will be created directly on your GitLab account.
๐ญ Web app allowing students to write reviews on some exams in order to help other students in preparing for those exams.
๐ Implementation of the famous Geometric Algebra Transformer to deal with geometric data. A modification of its attention module has been performed to study the equivariance of the architecture.
๐ฅ This project aims to deform the shape of an input mesh by following a set of 2D guidance images representing the desired output mesh. We use Pytorch3D and exploit a neural network to predict the shape deformation.
๐ฆฟ A reactive architecture made up of three controllers allows Tiago Robot to grasp and place a static object on-the-move (i.e. without stopping). The results are more gracefulness in the entire task execution and a minor task execution time.
๐ Implementation of homeworks for the Hot Topics in NLP course of the Master degree in Artificial Intelligence & Robotics at Sapienza University of Rome.
๐ฆพ This project consists of a ROS support for a Multi-robot simulator written in C++.
๐ฆพ Implementation of Lagrangian Neural Network tested on one-single link rigid robot and one-single link elastic robot.
๐ Two modifications of METER attention module are proposed and implemented to build two more efficient versions: Meta-METER and Pyra-METER.
๐งฒ This project presents the architecture and application of the Uformer neural network.
Published in International Conference on Image Analysis and Processing, 2023
Recommended citation: Schiavella, C., Cirillo, L., Papa, L., Russo, P., & Amerini, I. (2023, September). Optimize Vision Transformer Architecture via Efficient Attention Modules: A Study on the Monocular Depth Estimation Task. In International Conference on Image Analysis and Processing (pp. 383-394). Cham: Springer Nature Switzerland.
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Master in Artificial Intelligence & Robotics, Sapienza University of Rome, Department of Computer, Automatic and Management Engineering (DIAG), 2025
Teacher Assistant of the Computer Vision course held by Prof. Irene Amerini.
For any information about the practical lessons and related Google Colab notebooks, contact me at cirillo@diag.uniroma1.it