Results 71 to 80 of about 28,970 (210)

Advanced Capsule Networks via Context Awareness

open access: yes, 2019
Capsule Networks (CN) offer new architectures for Deep Learning (DL) community. Though its effectiveness has been demonstrated in MNIST and smallNORB datasets, the networks still face challenges in other datasets for images with distinct contexts.
Phong, Nguyen Huu, Ribeiro, Bernardete
core   +1 more source

DenseNet-FPA: Integrating DenseNet and Flower Pollination Algorithm for Breast Cancer Histopathology Image Classification

open access: yesIEEE Access
Breast cancer is one of the most prevalent and life-threatening diseases affecting women worldwide. Early and accurate diagnosis is critical for effective treatment and improved patient outcomes. While histopathological image analysis plays a key role in breast cancer diagnosis, the complexity and heterogeneity of these images present significant ...
Musa Adamu Wakili   +5 more
openaire   +2 more sources

AML‐Net: Attention‐based multi‐scale lightweight model for brain tumour segmentation in internet of medical things

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam   +3 more
wiley   +1 more source

Dilated DenseNets for Relational Reasoning

open access: yes, 2018
Despite their impressive performance in many tasks, deep neural networks often struggle at relational reasoning. This has recently been remedied with the introduction of a plug-in relational module that considers relations between pairs of objects. Unfortunately, this is combinatorially expensive.
Antoniou, Antreas   +3 more
openaire   +2 more sources

Review on enhancing clinical decision support system using machine learning

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract Clinical decision‐making is a complex patient‐centred process. For an informed clinical decision, the input data is very thorough ranging from detailed family history, environmental history, social history, health‐risk assessments, and prior relevant medical cases.
Anum Masood   +4 more
wiley   +1 more source

Research on wind turbine blade fault detection based on DenseNet-TL combined with ELM

open access: yesJournal of Applied Science and Engineering
Aiming at the safety hidden danger caused by blade faults that are difficult to be detected, the fault prevention detection technology based on blade image intelligent processing is investigated.
Dianming WANG   +6 more
doaj   +1 more source

Water Identification from High-Resolution Remote Sensing Images Based on Multidimensional Densely Connected Convolutional Neural Networks

open access: yesRemote Sensing, 2020
The accurate acquisition of water information from remote sensing images has become important in water resources monitoring and protections, and flooding disaster assessment.
Guojie Wang   +3 more
doaj   +1 more source

ECG‐TransCovNet: A hybrid transformer model for accurate arrhythmia detection using Electrocardiogram signals

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
Abstract Abnormalities in the heart's rhythm, known as arrhythmias, pose a significant threat to global health, often leading to severe cardiac conditions and sudden cardiac deaths. Therefore, early and accurate detection of arrhythmias is crucial for timely intervention and potentially life‐saving treatment.
Hasnain Ali Shah   +4 more
wiley   +1 more source

Multitype Game Optimisation: A Two‐Stage Fine‐Tuning Framework for Multi‑Game Optimisation With Large Language Models

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Large language models (LLMs) have made remarkable advances in natural language processing, demonstrating great potential in modelling structured sequences. However, adapting these capabilities to machine gaming tasks such as Go remains challenging due to limitations in strategy generalisation and optimisation efficiency.
Xiali Li   +5 more
wiley   +1 more source

Double‐Integration‐Enhanced Stochastic Gradient Descent Based on Neural Dynamics for Improving Generalisation

open access: yesCAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Generalisation is a crucial aspect of deep learning, enabling models to perform well on unseen data. Currently, most optimisers that improve generalisation typically suffer from efficiency bottlenecks. This paper proposes a double‐integration‐enhanced stochastic gradient descent (DIESGD) optimiser, which treats the negative gradient as an ...
Ting Li   +3 more
wiley   +1 more source

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