Search Results for author: Leonardo Rossi

Found 11 papers, 10 papers with code

Swin2-MoSE: A New Single Image Super-Resolution Model for Remote Sensing

2 code implementations29 Apr 2024 Leonardo Rossi, Vittorio Bernuzzi, Tomaso Fontanini, Massimo Bertozzi, Andrea Prati

Due to the limitations of current optical and sensor technologies and the high cost of updating them, the spectral and spatial resolution of satellites may not always meet desired requirements.

Multispectral Image Super-resolution Semantic Segmentation +1

Self-Balanced R-CNN for Instance Segmentation

1 code implementation25 Apr 2024 Leonardo Rossi, Akbar Karimi, Andrea Prati

Current state-of-the-art two-stage models on instance segmentation task suffer from several types of imbalances.

Instance Segmentation object-detection +2

LDD: A Dataset for Grape Diseases Object Detection and Instance Segmentation

no code implementations21 Jun 2022 Leonardo Rossi, Marco Valenti, Sara Elisabetta Legler, Andrea Prati

The Instance Segmentation task, an extension of the well-known Object Detection task, is of great help in many areas, such as precision agriculture: being able to automatically identify plant organs and the possible diseases associated with them, allows to effectively scale and automate crop monitoring and its diseases control.

Instance Segmentation Object +4

Improving Localization for Semi-Supervised Object Detection

1 code implementation21 Jun 2022 Leonardo Rossi, Akbar Karimi, Andrea Prati

Nowadays, Semi-Supervised Object Detection (SSOD) is a hot topic, since, while it is rather easy to collect images for creating a new dataset, labeling them is still an expensive and time-consuming task.

Object object-detection +3

AEDA: An Easier Data Augmentation Technique for Text Classification

1 code implementation Findings (EMNLP) 2021 Akbar Karimi, Leonardo Rossi, Andrea Prati

This is an easier technique to implement for data augmentation than EDA method (Wei and Zou, 2019) with which we compare our results.

Data Augmentation Sentence +2

Recursively Refined R-CNN: Instance Segmentation with Self-RoI Rebalancing

1 code implementation3 Apr 2021 Leonardo Rossi, Akbar Karimi, Andrea Prati

Within the field of instance segmentation, most of the state-of-the-art deep learning networks rely nowadays on cascade architectures, where multiple object detectors are trained sequentially, re-sampling the ground truth at each step.

Instance Segmentation Object Detection +1

UniParma at SemEval-2021 Task 5: Toxic Spans Detection Using CharacterBERT and Bag-of-Words Model

1 code implementation SEMEVAL 2021 Akbar Karimi, Leonardo Rossi, Andrea Prati

We tackle this problem utilizing a combination of a state-of-the-art pre-trained language model (CharacterBERT) and a traditional bag-of-words technique.

Language Modelling Toxic Spans Detection

A novel Region of Interest Extraction Layer for Instance Segmentation

5 code implementations28 Apr 2020 Leonardo Rossi, Akbar Karimi, Andrea Prati

Given the wide diffusion of deep neural network architectures for computer vision tasks, several new applications are nowadays more and more feasible.

Instance Segmentation object-detection +3

Adversarial Training for Aspect-Based Sentiment Analysis with BERT

4 code implementations30 Jan 2020 Akbar Karimi, Leonardo Rossi, Andrea Prati

In this work, we apply adversarial training, which was put forward by Goodfellow et al. (2014), to the post-trained BERT (BERT-PT) language model proposed by Xu et al. (2019) on the two major tasks of Aspect Extraction and Aspect Sentiment Classification in sentiment analysis.

Aspect-Based Sentiment Analysis Aspect Extraction +2

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