Matias Valdenegro-Toro

research

∙ 06/04/2023

Sanity Checks for Saliency Methods Explaining Object Detectors

Saliency methods are frequently used to explain Deep Neural Network-base...

0 Deepan Chakravarthi Padmanabhan, et al. ∙

research

∙ 12/21/2022

DExT: Detector Explanation Toolkit

State-of-the-art object detectors are treated as black boxes due to thei...

0 Deepan Chakravarthi Padmanabhan, et al. ∙

research

∙ 11/11/2022

Disentangled Uncertainty and Out of Distribution Detection in Medical Generative Models

Trusting the predictions of deep learning models in safety critical sett...

0 Kumud Lakara, et al. ∙

research

∙ 11/11/2022

A Benchmark for Out of Distribution Detection in Point Cloud 3D Semantic Segmentation

Safety-critical applications like autonomous driving use Deep Neural Net...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 11/11/2022

Comparison of Uncertainty Quantification with Deep Learning in Time Series Regression

Increasingly high-stakes decisions are made using neural networks in ord...

0 Levente Foldesi, et al. ∙

research

∙ 09/07/2022

Machine Learning Students Overfit to Overfitting

Overfitting and generalization is an important concept in Machine Learni...

48 Matias Valdenegro-Toro, et al. ∙

research

∙ 04/20/2022

Self-supervised Learning for Sonar Image Classification

Self-supervised learning has proved to be a powerful approach to learn i...

16 Alan Preciado-Grijalva, et al. ∙

research

∙ 04/20/2022

A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement

Neural networks are ubiquitous in many tasks, but trusting their predict...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 12/06/2021

Feature Disentanglement of Robot Trajectories

Modeling trajectories generated by robot joints is complex and required ...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 12/05/2021

Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning

Reinforcement Learning (RL) based solutions are being adopted in a varie...

0 Aaqib Parvez Mohammed, et al. ∙

research

∙ 11/18/2021

Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings

Uncertainty quantification in neural network promises to increase safety...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 09/28/2021

The VVAD-LRS3 Dataset for Visual Voice Activity Detection

Robots are becoming everyday devices, increasing their interaction with ...

1 Adrian Lubitz, et al. ∙

research

∙ 08/19/2021

Teaching Uncertainty Quantification in Machine Learning through Use Cases

Uncertainty in machine learning is not generally taught as general knowl...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 08/15/2021

The Marine Debris Dataset for Forward-Looking Sonar Semantic Segmentation

Accurate detection and segmentation of marine debris is important for ke...

0 Deepak Singh, et al. ∙

research

∙ 08/05/2021

Deep Reinforcement Learning for Continuous Docking Control of Autonomous Underwater Vehicles: A Benchmarking Study

Docking control of an autonomous underwater vehicle (AUV) is a task that...

0 Mihir Patil, et al. ∙

research

∙ 08/02/2021

Pre-trained Models for Sonar Images

Machine learning and neural networks are now ubiquitous in sonar percept...

7 Matias Valdenegro-Toro, et al. ∙

research

∙ 08/02/2021

Forward-Looking Sonar Patch Matching: Modern CNNs, Ensembling, and Uncertainty

Application of underwater robots are on the rise, most of them are depen...

4 Arka Mallick, et al. ∙

research

∙ 04/16/2021

I Find Your Lack of Uncertainty in Computer Vision Disturbing

Neural networks are used for many real world applications, but often the...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 12/02/2020

Are Gradient-based Saliency Maps Useful in Deep Reinforcement Learning?

Deep Reinforcement Learning (DRL) connects the classic Reinforcement Lea...

11 Matthias Rosynski, et al. ∙

research

∙ 11/23/2020

Unsupervised Difficulty Estimation with Action Scores

Evaluating difficulty and biases in machine learning models has become o...

0 Octavio Arriaga, et al. ∙

research

∙ 11/23/2020

Automatic Detection and Classification of Tick-borne Skin Lesions using Deep Learning

Around the globe, ticks are the culprit of transmitting a variety of bac...

0 Lauren Michelle Pfeifer, et al. ∙

research

∙ 10/29/2020

Black-Box Optimization of Object Detector Scales

Object detectors have improved considerably in the last years by using a...

0 Mohandass Muthuraja, et al. ∙

research

∙ 10/27/2020

Perception for Autonomous Systems (PAZ)

In this paper we introduce the Perception for Autonomous Systems (PAZ) s...

0 Octavio Arriaga, et al. ∙

research

∙ 10/27/2020

Can Reinforcement Learning for Continuous Control Generalize Across Physics Engines?

Reinforcement learning (RL) algorithms should learn as much as possible ...

0 Aaqib Parvez Mohammed, et al. ∙

research

∙ 10/27/2020

Know Where To Drop Your Weights: Towards Faster Uncertainty Estimation

Estimating epistemic uncertainty of models used in low-latency applicati...

0 Akshatha Kamath, et al. ∙

research

∙ 08/17/2020

Hey Human, If your Facial Emotions are Uncertain, You Should Use Bayesian Neural Networks!

Facial emotion recognition is the task to classify human emotions in fac...

0 Maryam Matin, et al. ∙

research

∙ 07/03/2020

Evaluating Uncertainty Estimation Methods on 3D Semantic Segmentation of Point Clouds

Deep learning models are extensively used in various safety critical app...

0 Swaroop Bhandary K, et al. ∙

research

∙ 10/29/2019

Results from the Robocademy ITN: Autonomy, Disturbance Rejection and Perception for Advanced Marine Robotics

Marine and Underwater resources are important part of the economy of man...

7 Matias Valdenegro-Toro, et al. ∙

research

∙ 10/17/2019

Deep Sub-Ensembles for Fast Uncertainty Estimation in Image Classification

Fast estimates of model uncertainty are required for many robust robotic...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 07/01/2019

Learning Objectness from Sonar Images for Class-Independent Object Detection

Detecting novel objects without class information is not trivial, as it ...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 05/13/2019

Deep Neural Networks for Marine Debris Detection in Sonar Images

Garbage and waste disposal is one of the biggest challenges currently fa...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 03/28/2019

Implementing Noise with Hash functions for Graphics Processing Units

We propose a modification to Perlin noise which use computable hash func...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 07/11/2018

Modeling and Soft-fault Diagnosis of Underwater Thrusters with Recurrent Neural Networks

Noncritical soft-faults and model deviations are a challenge for Fault D...

0 Samy Nascimento, et al. ∙

research

∙ 11/07/2017

Image Captioning and Classification of Dangerous Situations

Current robot platforms are being employed to collaborate with humans in...

0 Octavio Arriaga, et al. ∙

research

∙ 10/20/2017

Real-time Convolutional Neural Networks for Emotion and Gender Classification

In this paper we propose an implement a general convolutional neural net...

0 Octavio Arriaga, et al. ∙

research

∙ 09/08/2017

Best Practices in Convolutional Networks for Forward-Looking Sonar Image Recognition

Convolutional Neural Networks (CNN) have revolutionized perception for c...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 09/08/2017

Objectness Scoring and Detection Proposals in Forward-Looking Sonar Images with Convolutional Neural Networks

Forward-looking sonar can capture high resolution images of underwater s...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 09/07/2017

Real-time convolutional networks for sonar image classification in low-power embedded systems

Deep Neural Networks have impressive classification performance, but thi...

0 Matias Valdenegro-Toro, et al. ∙

research

∙ 09/07/2017

Improving Sonar Image Patch Matching via Deep Learning

Matching sonar images with high accuracy has been a problem for a long t...

0 Matias Valdenegro-Toro, et al. ∙

Matias Valdenegro-Toro

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