A systematic review of compressive sensing: Concepts, implementations and applications

M Rani, SB Dhok, RB Deshmukh - IEEE access, 2018 - ieeexplore.ieee.org
Compressive Sensing (CS) is a new sensing modality, which compresses the signal being
acquired at the time of sensing. Signals can have sparse or compressible representation …

Systematic map** of global research on climate and health: a machine learning review

L Berrang-Ford, AJ Sietsma, M Callaghan… - The Lancet Planetary …, 2021 - thelancet.com
Background The global literature on the links between climate change and human health is
large, increasing exponentially, and it is no longer feasible to collate and synthesise using …

Craft: Concept recursive activation factorization for explainability

T Fel, A Picard, L Bethune, T Boissin… - Proceedings of the …, 2023 - openaccess.thecvf.com
Attribution methods are a popular class of explainability methods that use heatmaps to
depict the most important areas of an image that drive a model decision. Nevertheless …

Padchest: A large chest x-ray image dataset with multi-label annotated reports

A Bustos, A Pertusa, JM Salinas… - Medical image …, 2020 - Elsevier
We present a labeled large-scale, high resolution chest x-ray dataset for the automated
exploration of medical images along with their associated reports. This dataset includes …

[SÁCH][B] Neural networks and statistical learning

KL Du, MNS Swamy - 2013 - books.google.com
Providing a broad but in-depth introduction to neural network and machine learning in a
statistical framework, this book provides a single, comprehensive resource for study and …