Results 41 to 50 of about 2,716,934 (278)

Inequality in breast cancer: Global statistics from 2022 to 2050

open access: yesBreast
This study evaluates the global inequalities of breast cancer incidence and mortality from 2022 to 2050 with the latest GLOBOCAN estimates. It focuses on disparities across continents, age groups and Human Development Index (HDI) levels.
Ling Liao
doaj   +1 more source

Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning

open access: yesBMC Medical Informatics and Decision Making, 2019
Background With the advancement of powerful image processing and machine learning techniques, Computer Aided Diagnosis has become ever more prevalent in all fields of medicine including ophthalmology.
Muhammad Naseer Bajwa   +6 more
doaj   +1 more source

A Deep Learning Enabled Multi-Class Plant Disease Detection Model Based on Computer Vision

open access: yesAI, 2021
In this paper, a deep learning enabled object detection model for multi-class plant disease has been proposed based on a state-of-the-art computer vision algorithm. While most existing models are limited to disease detection on a large scale, the current
Arunabha M. Roy, Jayabrata Bhaduri
doaj   +1 more source

Modular Deep Learning

open access: yesTrans. Mach. Learn. Res., 2023
Transfer learning has recently become the dominant paradigm of machine learning. Pre-trained models fine-tuned for downstream tasks achieve better performance with fewer labelled examples. Nonetheless, it remains unclear how to develop models that specialise towards multiple tasks without incurring negative interference and that generalise ...
Jonas Pfeiffer   +3 more
openaire   +3 more sources

UCL: Unsupervised Curriculum Learning for water body classification from remote sensing imagery

open access: yesInternational Journal of Applied Earth Observations and Geoinformation, 2021
This paper presents a Convolutional Neural Networks (CNN) based Unsupervised Curriculum Learning approach for the recognition of water bodies to overcome the stated challenges for remote sensing based RGB imagery. The unsupervised nature of the presented
Nosheen Abid   +6 more
doaj   +1 more source

Multi-Strategy Improved Red-Tailed Hawk Algorithm for Real-Environment Unmanned Aerial Vehicle Path Planning

open access: yesBiomimetics
In recent years, unmanned aerial vehicle (UAV) technology has advanced significantly, enabling its widespread use in critical applications such as surveillance, search and rescue, and environmental monitoring.
Mingen Wang   +6 more
doaj   +1 more source

The human gut microbiome across the life course

open access: yesFEBS Letters, EarlyView.
Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero   +4 more
wiley   +1 more source

Performance Evaluation of Deep Learning Tools in Docker Containers

open access: yes, 2017
With the success of deep learning techniques in a broad range of application domains, many deep learning software frameworks have been developed and are being updated frequently to adapt to new hardware features and software libraries, which bring a big ...
Chu, Xiaowen, Shi, Shaohuai, Xu, Pengfei
core   +1 more source

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

open access: yesMolecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee   +8 more
wiley   +1 more source

Deep learning microscopy

open access: yesOptica, 2017
We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired using a regular optical microscope, without any changes to its design.
Yair Rivenson   +5 more
openaire   +3 more sources

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