Suchergebnisse - stacked sparse denoising autoencoder network (sUDAN)

A Systematic Review of Advances in Deep Learning Architectures for Efficient and Sustainable Photovoltaic Solar Tracking: Research Challenges and Future Directions.

Autoren: Alhazmi, Ali Maswadi, Kholoud Eke, Christopher Ifeanyi

Quelle: Sustainability (2071-1050); Nov2025, Vol. 17 Issue 21, p9625, 44p

Deep Learning-Enhanced Spectroscopic Technologies for Food Quality Assessment: Convergence and Emerging Frontiers.

Autoren: Lun, Zhichen Wu, Xiaohong Dong, Jiajun et al.

Quelle: Foods; Jul2025, Vol. 14 Issue 13, p2350, 36p

Schlagwörter: DEEP learning, FOOD quality, ARTIFICIAL intelligence, NONDESTRUCTIVE testing, MULTISENSOR data fusion, EDGE computing, SPECTRAL imaging

Machine and deep learning techniques for the prediction of diabetics: a review.

Autoren: Modak, Sandip Kumar Singh Jha, Vijay Kumar

Quelle: Multimedia Tools & Applications; May2025, Vol. 84 Issue 18, p19425-19549, 125p

Schlagwörter: ARTIFICIAL intelligence, MACHINE learning, DATA mining, METABOLIC disorders, DIAGNOSIS, DEEP learning

MGFEEN: a multi-granularity feature encoding ensemble network for remote sensing image classification.

Autoren: Jean Bosco, Musabe Jean Pierre, Rutarindwa Muthanna, Mohammed Saleh Ali et al.

Quelle: Neural Computing & Applications; Apr2024, Vol. 36 Issue 12, p6547-6558, 12p

Schlagwörter: IMAGE recognition (Computer vision), CONVOLUTIONAL neural networks, FEATURE extraction, ENCODING, RESEARCH personnel

Firma/Körperschaft: UNIVERSITY of California, Merced

Flood susceptibility mapping and assessment using a novel deep learning model combining multilayer perceptron and autoencoder neural networks.

Autoren: Ahmadlou, Mohammad Al‐Fugara, A'kif Al‐Shabeeb, Abdel Rahman et al.

Quelle: Journal of Flood Risk Management; Mar2021, Vol. 14 Issue 1, p1-22, 22p

Schlagwörter: DEEP learning, GEOGRAPHIC information systems, RECEIVER operating characteristic curves, FLOODS, REMOTE sensing

Geografische Kategorien: IRAN, INDIA

Incremental autoencoders for text streams clustering in social networks.

Autoren: Rekik, Amal Jamoussi, Salma

Quelle: Journal of Universal Computer Science (JUCS); 2021, Vol. 27 Issue 11, p1203-1221, 19p

A Survey of Recent Advances in Deep Learning Models for Detecting Malware in Desktop and Mobile Platforms.

Autoren: Maniriho, Pascal Mahmood, Abdun Naser Chowdhury, Mohammad Jabed Morshed

Quelle: ACM Computing Surveys; Jun2024, Vol. 56 Issue 6, p1-41, 41p

Schlagwörter: LANGUAGE models, DEEP learning, ARTIFICIAL neural networks, REINFORCEMENT learning, ARTIFICIAL intelligence, MACHINE learning

Artificial intelligence in geoenergy: bridging petroleum engineering and future-oriented applications.

Autoren: Kim, Sungil Kim, Tea-Woo Jo, Suryeom

Quelle: Journal of Petroleum Exploration & Production Technology; Feb2025, Vol. 15 Issue 2, p1-60, 60p

Semi‐supervised deep autoencoder for seismic facies classification.

Autoren: Liu, Xingye Li, Bin Li, Jingye et al.

Quelle: Geophysical Prospecting; Jul2021, Vol. 69 Issue 6, p1295-1315, 21p

Schlagwörter: SUPERVISED learning, FACIES, DEEP learning, CLASSIFICATION

European Heart Journal (2024) 45 (Suppl 1).

Quelle: European Heart Journal; 2024 Supplement, Vol. 45, p1-5865, 5865p

Schlagwörter: MEDICAL sciences, GLOBAL longitudinal strain, VENA cava inferior, LEFT heart ventricle, HEART septum, HEART failure, STRESS echocardiography, ACOUSTIC radiation force impulse imaging

A comprehensive survey on optimizing deep learning models by metaheuristics.

Autoren: Akay, Bahriye Karaboga, Dervis Akay, Rustu

Quelle: Artificial Intelligence Review; Feb2022, Vol. 55 Issue 2, p829-894, 66p

Schlagwörter: DEEP learning, METAHEURISTIC algorithms, ARTIFICIAL neural networks, RECURRENT neural networks, CONVOLUTIONAL neural networks

Advanced metaheuristic optimization techniques in applications of deep neural networks: a review.

Autoren: Abd Elaziz, Mohamed Dahou, Abdelghani Abualigah, Laith et al.

Quelle: Neural Computing & Applications; Nov2021, Vol. 33 Issue 21, p14079-14099, 21p

Schlagwörter: METAHEURISTIC algorithms, MATHEMATICAL optimization, SWARM intelligence, MACHINE learning, DEEP learning, TASK performance

Automatic Seismic Lithology Interpretation via Multiattribute Integrated Deep Learning.

Autoren: Pan, Lele Gao, Jinghuai Yang, Yang et al.

Quelle: IEEE Geoscience & Remote Sensing Letters; 2023, Vol. 20, p1-5, 5p

A survey of swarm and evolutionary computing approaches for deep learning.

Autoren: Darwish, Ashraf Hassanien, Aboul Ella Das, Swagatam

Quelle: Artificial Intelligence Review; Mar2020, Vol. 53 Issue 3, p1767-1812, 46p

Schlagwörter: ARTIFICIAL neural networks, SWARM intelligence, LARGE scale systems, EVOLUTIONARY computation, DEEP learning, BIG data, MACHINE learning

Ultrasound-Based Image Analysis for Predicting Carotid Artery Stenosis Risk: A Comprehensive Review of the Problem, Techniques, Datasets, and Future Directions.

Autoren: Ottakath, Najmath Al-Maadeed, Somaya Zughaier, Susu M. et al.

Quelle: Diagnostics (2075-4418); Aug2023, Vol. 13 Issue 15, p2614, 33p

Schlagwörter: CAROTID artery stenosis, IMAGE analysis, CAROTID intima-media thickness, CAROTID artery, DEEP learning

Spatial analysis of environmental factors influencing dust sources in the east of Iran using a new activelearning approach.

Autoren: Yariyan, Peyman Amiri, Mahdis Saffariha, Maryam et al.

Quelle: Geocarto International; 2022, Vol. 37 Issue 26, p11929-11954, 26p

Schlagwörter: FACTOR analysis, DUST storms, WIND speed, DUST

Geografische Kategorien: IRAN

Integration of ASTER and Soil Survey Data by Principal Components Analysis and One-Class Support Vector Machine for Mineral Prospectivity Mapping in Kerkasha, Southwestern Eritrea.

Autoren: Zerai, Finhas Tsehaye Gorsevski, Pece V. Panter, Kurt S. et al.

Quelle: Natural Resources Research; Dec2023, Vol. 32 Issue 6, p2463-2493, 31p

Schlagwörter: PRINCIPAL components analysis, SUPPORT vector machines, SOIL surveys, HYDROTHERMAL alteration, RECEIVER operating characteristic curves

Geografische Kategorien: ERITREA

Book of Abstracts ESMRMB 2023 Online 39th Annual Scientific Meeting 4–7 October 2023.

Quelle: MAGMA: Magnetic Resonance Materials in Physics, Biology & Medicine; 2023 Suppl 1, Vol. 36 Issue 1, p1-328, 328p

Schlagwörter: ANNUAL meetings

Over a decade of social opinion mining: a systematic review.

Autoren: Cortis, Keith Davis, Brian

Quelle: Artificial Intelligence Review; Oct2021, Vol. 54 Issue 7, p4873-4965, 93p

Schlagwörter: USER-generated content, SENTIMENT analysis, NATURAL language processing, NATURAL languages, SOCIAL media, ARTIFICIAL intelligence

Google Earth Engine and Artificial Intelligence (AI): A Comprehensive Review.

Autoren: Yang, Liping Driscol, Joshua Sarigai, Sarigai et al.

Quelle: Remote Sensing; Jul2022, Vol. 14 Issue 14, pN.PAG-N.PAG, 110p

Schlagwörter: ARTIFICIAL intelligence, CLIMATE change, GEOSPATIAL data, WEB-based user interfaces, WEB design, HAZARD Analysis & Critical Control Point (Food safety system)