Results 51 to 60 of about 247,960 (211)
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
Advanced Intelligent Discovery, EarlyView.The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
AE-MLP: A hybrid deep learning approach for DDoS detection and classification
, 2021 Distributed Denial-of-Service (DDoS) attacks are increasing as the demand for Internet connectivity massively grows in recent years. Conventional shallow machine learning-based techniques for DDoS attack classification tend to be ineffective when the ...
Yuanyuan Wei (233952) +5 more
core +1 more source
Hyperspectral anomaly detection via memory‐augmented autoencoders
CAAI Transactions on Intelligence Technology, 2023 Recently, the autoencoder (AE) based method plays a critical role in the hyperspectral anomaly detection domain. However, due to the strong generalised capacity of AE, the abnormal samples are usually reconstructed well along with the normal background ...
Zhe Zhao, Bangyong Sun
doaj +1 more source
Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The overlapping and imbalanced data in classification present key challenges. Class‐separable extreme learning machine auto‐encoding (CS‐ELM‐AE) is proposed, which is an enhancement of ELM‐AE that better handles overlapping data by clustering points from the same class together. Applying oversampling addresses imbalanced data.
Ekkarat Boonchieng, Wanchaloem Nadda
wiley +1 more source
Asia-Pacific Journal of Chemical Engineering, EarlyView.ABSTRACT Air pollution from sulfur dioxide (SO2) emissions poses significant threats to environmental sustainability, public health, and climate change efforts. Despite advances in monitoring and regulatory frameworks, traditional methods often fall short in accuracy, scalability, and efficiency.
Turkan Kopac
wiley +1 more source
Health Prognostics Classification with Autoencoders for Predictive Maintenance of HVAC Systems
Energies, 2023 Buildings’ heating, ventilation, and air-conditioning (HVAC) systems account for significant global energy use. Proper maintenance can minimize their environmental footprint and enhance the quality of the indoor environment.
Ruiqi Tian +2 more
doaj +1 more source
Med Research, EarlyView.This review details a three‐stage paradigm shift for tumor‐reactive CD8+ T‐cell identification: decoding transcriptomic states, deciphering clonal functional efficacy, and molecular‐level therapeutic TCR design. Addressing translational hurdles and generative AI “scientific blind spots”—such as missing catch bonds—we present a visionary roadmap.
Chao Yang +4 more
wiley +1 more source
A tutorial on multi-view autoencoders using the multi-view-AE library
CoRRThere has been a growing interest in recent years in modelling multiple modalities (or views) of data to for example, understand the relationship between modalities or to generate missing data. Multi-view autoencoders have gained significant traction for their adaptability and versatility in modelling multi-modal data, demonstrating an ability to ...
Ana Lawry Aguila, André Altmann
openaire +2 more sources
Similarity‐Driven Framework for Efficient Polymer Property Prediction Under Data Scarcity Scenarios
Journal of Polymer Science, EarlyView.A new approach, based on structural and chemical similarities between polymers, is proposed to improve the performance of artificial neural networks in predicting the glass transition temperature under data‐scarce conditions. ABSTRACT Predicting polymer properties directly from chemical structure is essential for the rational design of advanced ...
Amaia Elizaran Mendarte +1 more
wiley +1 more source
Video Anomaly Detection Based on Convolutional Recurrent AutoEncoder
Sensors, 2022 As an essential task in computer vision, video anomaly detection technology is used in video surveillance, scene understanding, road traffic analysis and other fields.
Bokun Wang, Caiqian Yang
doaj +1 more source