853 citations · 1.5k across the 31 of their papers we have counts for
18 papers · 1 filter
Cross-Camera Distracted Driver Classification through Feature Disentanglement and Contrastive Learning
Luigi Celona, Simone Bianco, Paolo Napoletano
The classification of distracted drivers is pivotal for ensuring safe driving. Previous studies demonstrated the effectiveness of neural networks in automatically predicting driver…
Improving Image Captioning Descriptiveness by Ranking and LLM-based Fusion
Luigi Celona, Simone Bianco, Marco Donzella +1
State-of-The-Art (SoTA) image captioning models are often trained on the MicroSoft Common Objects in Context (MS-COCO) dataset, which contains human-annotated captions with an aver…
Unsupervised Deep Learning-based clustering for Human Activity Recognition
Hamza Amrani, Daniela Micucci, Paolo Napoletano
One of the main problems in applying deep learning techniques to recognize activities of daily living (ADLs) based on inertial sensors is the lack of appropriately large labelled d…
A deep scalable neural architecture for soil properties estimation from spectral information
Flavio Piccoli, Micol Rossini, Roberto Colombo +2
In this paper we propose an adaptive deep neural architecture for the prediction of multiple soil characteristics from the analysis of hyperspectral signatures. The proposed method…
Unsupervised Segmentation of Hyperspectral Remote Sensing Images with Superpixels
Mirko Paolo Barbato, Paolo Napoletano, Flavio Piccoli +1
In this paper, we propose an unsupervised method for hyperspectral remote sensing image segmentation. The method exploits the mean-shift clustering algorithm that takes as input a…
Composition and Style Attributes Guided Image Aesthetic Assessment
Luigi Celona, Marco Leonardi, Paolo Napoletano +1
The aesthetic quality of an image is defined as the measure or appreciation of the beauty of an image. Aesthetics is inherently a subjective property but there are certain factors…
Personalization in Human Activity Recognition
Anna Ferrari, Daniela Micucci, Marco Mobilio +1
In the recent years there has been a growing interest in techniques able to automatically recognize activities performed by people. This field is known as Human Activity recognitio…
Disentangling Image Distortions in Deep Feature Space
Simone Bianco, Luigi Celona, Paolo Napoletano
Previous literature suggests that perceptual similarity is an emergent property shared across deep visual representations. Experiments conducted on a dataset of human-judged image…
Multitask Painting Categorization by Deep Multibranch Neural Network
Simone Bianco, Davide Mazzini, Paolo Napoletano +1
In this work we propose a new deep multibranch neural network to solve the tasks of artist, style, and genre categorization in a multitask formulation. In order to gather clues fro…
Benchmark Analysis of Representative Deep Neural Network Architectures
Simone Bianco, Remi Cadene, Luigi Celona +1
This work presents an in-depth analysis of the majority of the deep neural networks (DNNs) proposed in the state of the art for image recognition. For each DNN multiple performance…
Automated Pruning for Deep Neural Network Compression
Franco Manessi, Alessandro Rozza, Simone Bianco +2
In this work we present a method to improve the pruning step of the current state-of-the-art methodology to compress neural networks. The novelty of the proposed pruning technique…
UniMiB SHAR: a new dataset for human activity recognition using acceleration data from smartphones
Daniela Micucci, Marco Mobilio, Paolo Napoletano
Smartphones, smartwatches, fitness trackers, and ad-hoc wearable devices are being increasingly used to monitor human activities. Data acquired by the hosted sensors are usually pr…
On the Use of Deep Learning for Blind Image Quality Assessment
Simone Bianco, Luigi Celona, Paolo Napoletano +1
In this work we investigate the use of deep learning for distortion-generic blind image quality assessment. We report on different design choices, ranging from the use of features…
Visual descriptors for content-based retrieval of remote sensing images
Paolo Napoletano
In this paper we present an extensive evaluation of visual descriptors for the content-based retrieval of remote sensing (RS) images. The evaluation includes global hand-crafted, l…
Evaluating color texture descriptors under large variations of controlled lighting conditions
Claudio Cusano, Paolo Napoletano, Raimondo Schettini
The recognition of color texture under varying lighting conditions is still an open issue. Several features have been proposed for this purpose, ranging from traditional statistica…
IAT - Image Annotation Tool: Manual
Gianluigi Ciocca, Paolo Napoletano, Raimondo Schettini
The annotation of image and video data of large datasets is a fundamental task in multimedia information retrieval and computer vision applications. In order to support the users d…
Attentive monitoring of multiple video streams driven by a Bayesian foraging strategy
Paolo Napoletano, Giuseppe Boccignone, Francesco Tisato
In this paper we shall consider the problem of deploying attention to subsets of the video streams for collating the most relevant data and information of interest related to a giv…
Remote sensing image classification exploiting multiple kernel learning
Claudio Cusano, Paolo Napoletano, Raimondo Schettini
We propose a strategy for land use classification which exploits Multiple Kernel Learning (MKL) to automatically determine a suitable combination of a set of features without requi…