most citedDeep Radiomics for Brain Tumor Detection and Classification from Multi-Sequence MRI

41 citations · 64 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024★ 6 cited

Real-Time Detection of Electronic Components in Waste Printed Circuit Boards: A Transformer-Based Approach

Muhammad Mohsin, Stefano Rovetta, Francesco Masulli +1

Critical Raw Materials (CRMs) such as copper, manganese, gallium, and various rare earths have great importance for the electronic industry. To increase the concentration of indivi…

cs.HC2024★ 8 cited

A Cost-Effective Eye-Tracker for Early Detection of Mild Cognitive Impairment

Danilo Greco, Francesco Masulli, Stefano Rovetta +2

This paper presents a low-cost eye-tracker aimed at carrying out tests based on a Visual Paired Comparison protocol for the early detection of Mild Cognitive Impairment. The propos…

cs.CV2024★ 6 cited

Virtual Mines -- Component-level recycling of printed circuit boards using deep learning

Muhammad Mohsin, Stefano Rovetta, Francesco Masulli +1

This contribution gives an overview of an ongoing project using machine learning and computer vision components for improving the electronic waste recycling process. In circular ec…

cs.CV2024★ 3 cited

Measuring the Recyclability of Electronic Components to Assist Automatic Disassembly and Sorting Waste Printed Circuit Boards

Muhammad Mohsin, Xianlai Zeng, Stefano Rovetta +1

The waste of electrical and electronic equipment has been increased due to the fast evolution of technology products and competition of many IT sectors. Every year millions of tons…

cs.CV2019★ 41 cited

Deep Radiomics for Brain Tumor Detection and Classification from Multi-Sequence MRI

Subhashis Banerjee, Sushmita Mitra, Francesco Masulli +1

Glioma constitutes 80% of malignant primary brain tumors and is usually classified as HGG and LGG. The LGG tumors are less aggressive, with slower growth rate as compared to HGG, a…