Nicola Strisciuglio | DeepAI

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∙ 08/12/2023

DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut Learning

Neural networks are prone to learn easy solutions from superficial stati...

0 Shunxin Wang, et al. ∙

∙ 07/28/2023

Defocus Blur Synthesis and Deblurring via Interpolation and Extrapolation in Latent Space

Though modern microscopes have an autofocusing system to ensure optimal ...

0 Ioana Mazilu, et al. ∙

∙ 07/19/2023

What do neural networks learn in image classification? A frequency shortcut perspective

Frequency analysis is useful for understanding the mechanisms of represe...

0 Shunxin Wang, et al. ∙

∙ 05/22/2023

RSA-INR: Riemannian Shape Autoencoding via 4D Implicit Neural Representations

Shape encoding and shape analysis are valuable tools for comparing shape...

6 Sven Dummer, et al. ∙

∙ 05/10/2023

The Robustness of Computer Vision Models against Common Corruptions: a Survey

The performance of computer vision models is susceptible to unexpected c...

0 Shunxin Wang, et al. ∙

∙ 03/21/2023

Data-efficient Large Scale Place Recognition with Graded Similarity Supervision

Visual place recognition (VPR) is a fundamental task of computer vision ...

0 Maria Leyva-Vallina, et al. ∙

∙ 03/11/2021

Generalized Contrastive Optimization of Siamese Networks for Place Recognition

Visual place recognition is a challenging task in computer vision and a ...

13 Maria Leyva-Vallina, et al. ∙

∙ 03/02/2021

Brain-inspired algorithms for processing of visual data

The study of the visual system of the brain has attracted the attention ...

0 Nicola Strisciuglio, et al. ∙

∙ 06/27/2020

MTStereo 2.0: improved accuracy of stereo depth estimation withMax-trees

Efficient yet accurate extraction of depth from stereo image pairs is re...

6 Rafael Brandt, et al. ∙

∙ 06/28/2019

Place recognition in gardens by learning visual representations: data set and benchmark analysis

Visual place recognition is an important component of systems for camera...

2 Maria Leyva-Vallina, et al. ∙

∙ 01/29/2019

A Push-Pull Layer Improves Robustness of Convolutional Neural Networks

We propose a new layer in Convolutional Neural Networks (CNNs) to increa...

0 Nicola Strisciuglio, et al. ∙

∙ 01/21/2019

Learning sound representations using trainable COPE feature extractors

Sound analysis research has mainly been focused on speech and music proc...

0 Nicola Strisciuglio, et al. ∙

∙ 11/26/2018

Brain-inspired robust delineation operator

In this paper we present a novel filter, based on the existing COSFIRE f...

0 Nicola Strisciuglio, et al. ∙

∙ 04/05/2018

TrimBot2020: an outdoor robot for automatic gardening

Robots are increasingly present in modern industry and also in everyday ...

0 Nicola Strisciuglio, et al. ∙

∙ 01/02/2018

Learning audio and image representations with bio-inspired trainable feature extractors

Recent advancements in pattern recognition and signal processing concern...

0 Nicola Strisciuglio, et al. ∙

∙ 08/02/2017

Action recognition by learning pose representations

Pose detection is one of the fundamental steps for the recognition of hu...

0 Alessia Saggese, et al. ∙

∙ 07/24/2017

Detection of curved lines with B-COSFIRE filters: A case study on crack delineation

The detection of curvilinear structures is an important step for various...

0 Nicola Strisciuglio, et al. ∙

∙ 07/24/2017

Delineation of line patterns in images using B-COSFIRE filters

Delineation of line patterns in images is a basic step required in vario...

0 Nicola Strisciuglio, et al. ∙

∙ 03/29/2017

Sentiment Recognition in Egocentric Photostreams

Lifelogging is a process of collecting rich source of information about ...

0 Estefania Talavera, et al. ∙

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