Publications associées à Binary classification

Exploring neural networks and their potential for species distribution modeling

Devis Tuia, Benjamin Alexander Kellenberger, Nina Marion Aurélia Van Tiel, Robin Adrien Zbinden, Lloyd Haydn Hughes

Species distribution models (SDMs) relate species occurrence data with environmental variables and are used to understand and predict species distributions across landscapes. While some machine learning models have been adopted by the SDM community, recent ...

2023

Layer-Wise Learning Framework for Efficient DNN Deployment in Biomedical Wearable Systems

David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Alireza Amirshahi, Saleh Baghersalimi

The development of low-power wearable systems requires specialized techniques to accommodate their unique requirements and constraints. While significant advancements have been made in the inference phase of artificial intelligence, the training phase rema ...

2023

Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection

Alexandre Schmid, Keyvan Farhang Razi

Early and accurate detection of epileptic seizures is an extremely important therapeutic goal due to the severity of complications it can prevent. To this end, a low-power machine learning-based seizure detection implemented on an FPGA is proposed in this ...

IEEE2022

Dynamic Probabilistic Pruning: A General Framework for Hardware-Constrained Pruning at Different Granularities

Alexandre Schmid, Lizeth Gonzalez Carabarin

Unstructured neural network pruning algorithms have achieved impressive compression ratios. However, the resulting-typically irregular-sparse matrices hamper efficient hardware implementations, leading to additional memory usage and complex control logic t ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Robust Binary Models by Pruning Randomly-initialized Networks

Sabine Süsstrunk, Mathieu Salzmann, Chen Liu, Ziqi Zhao

Robustness to adversarial attacks was shown to require a larger model capacity, and thus a larger memory footprint. In this paper, we introduce an approach to obtain robust yet compact models by pruning randomly-initialized binary networks. Unlike adversar ...

2022

Decentralized Semi-supervised Learning over Multitask Graphs

Ali H. Sayed, Roula Nassif, Elsa Rizk

In network semi-supervised learning problems, only a subset of the network nodes is able to access the data labeling. This paper formulates a decentralized optimization problem where agents have individual decision rules to estimate, subject to the conditi ...

IEEE2022

Wearable Ultrasound Interface for Prosthetic Hand Manipulation

Xingchen Yang

Ultrasound can non-invasively detect muscle deformations, which has great potential applications in prosthetic hand control. This research developed a miniaturized ultrasound device that could be integrated into a prosthetic hand socket. This compact syste ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Improving filling level classification with adversarial training

Pascal Frossard, Andrea Cavallaro, Apostolos Modas

We investigate the problem of classifying — from a single image — the level of content in a cup or a drinking glass. This problem is made challenging by several ambiguities caused by transparencies, shape variations and partial occlusions, and by the avail ...

2021

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Binary classification

Exploring neural networks and their potential for species distribution modeling

Layer-Wise Learning Framework for Efficient DNN Deployment in Biomedical Wearable Systems

Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection

Dynamic Probabilistic Pruning: A General Framework for Hardware-Constrained Pruning at Different Granularities

Eigenvalue multiplicities of group elements in irreducible representations of simple linear algebraic groups

Robust Binary Models by Pruning Randomly-initialized Networks

Decentralized Semi-supervised Learning over Multitask Graphs

Contrastive Feature Learning for Railway Infrastructure Fault Diagnostic

Wearable Ultrasound Interface for Prosthetic Hand Manipulation

Improving filling level classification with adversarial training

Graph Chatbot

Chattez avec Graph Search

Robust Binary Models by Pruning Randomly-initialized Networks

Hardware-Friendly Random Forest Classification of iEEG Signals for Implantable Seizure Detection

Wearable Ultrasound Interface for Prosthetic Hand Manipulation

Dynamic Probabilistic Pruning: A General Framework for Hardware-Constrained Pruning at Different Granularities

Decentralized Semi-supervised Learning over Multitask Graphs

Contrastive Feature Learning for Railway Infrastructure Fault Diagnostic

Exploring neural networks and their potential for species distribution modeling

Eigenvalue multiplicities of group elements in irreducible representations of simple linear algebraic groups

Layer-Wise Learning Framework for Efficient DNN Deployment in Biomedical Wearable Systems

Improving filling level classification with adversarial training