Suchergebnisse - "Flexible Dwarf Mongoose Optimization Algorithm"

Hybrid convolutional neural network and Flexible Dwarf Mongoose Optimization Algorithm for strong kidney stone diagnosis

Autoren: Haozhi Liu Noradin Ghadimi

Quelle: Biomedical Signal Processing and Control. 91:106024

Hybrid convolutional neural network and Flexible Dwarf Mongoose Optimization Algorithm for strong kidney stone diagnosis.

Autoren: Liu, Haozhi Ghadimi, Noradin

Quelle: Biomedical Signal Processing & Control. May2024, Vol. 91, pN.PAG-N.PAG. 1p.

Schlagwörter: Convolutional neural networks, Kidney stones diagnosis, Optimization algorithms, Mongooses, Data augmentation, Kidney stones

Researchers from Huazhong University of Science and Technology Report New Studies and Findings in the Area of Engineering (Hybrid Convolutional Neural Network and Flexible Dwarf Mongoose Optimization Algorithm for Strong Kidney Stone Diagnosis).

Quelle: Health & Medicine Week. 5/10/2024, p5695-5695. 1p.

Adaptive Dual-Channel Neural Network with Triangulation Topology Optimization for Kidney Cancer Diagnosis and Surgery Planning Using Clinical Metadata.

Autoren: Harshavardhan, A. Shaikh, Rafik Jamil Nabilal, Khan Vajid et al.

Quelle: Sensing & Imaging; 11/26/2025, Vol. 26 Issue 1, p1-35, 35p

Deep learning with refined single candidate optimizer for early polyp detection.

Autoren: Wen, Guoyi Yan, Jiayu Chen, Xin et al.

Quelle: Scientific Reports; 11/18/2025, Vol. 15 Issue 1, p1-23, 23p

Schlagwörter: COLORECTAL cancer, COLONOSCOPY, DEEP learning, COLON polyps, MATHEMATICAL optimization, SUPPORT vector machines, FEATURE extraction

Contour‐Detected Normalized Residual Model for Kidney Stone Classification.

Autoren: M., Shyamala Devi Natarajan, Yuvaraj S., Priya et al.

Quelle: Applied Computational Intelligence & Soft Computing; 11/4/2025, Vol. 2025, p1-37, 37p

Schlagwörter: KIDNEY stones, DEEP learning, COMPUTER-aided diagnosis, EDGE detection (Image processing), CONVOLUTIONAL neural networks, COMPUTER-assisted image analysis (Medicine), ARTIFICIAL neural networks, IMAGE recognition (Computer vision)

An optimized bidirectional recurrent neural network for kidney stone detection based on developed bald eagle search method in CT scan images.

Autoren: Tang, Zhenyou Tang, Zhenyu Liu, Yuxin et al.

Quelle: Scientific Reports; 10/23/2025, Vol. 15 Issue 1, p1-18, 18p

Schlagwörter: KIDNEY stones, DEEP learning, DATA augmentation, ARTIFICIAL neural networks, COMPUTED tomography, METAHEURISTIC algorithms, COMPUTER-assisted image analysis (Medicine), DETECTION algorithms

Enhancing kidney stone diagnosis with AI-driven radiographic imaging: a review.

Autoren: Vasudeva, Nisha Dhaka, Vijaypal Singh Sinwar, Deepak

Quelle: Discover Artificial Intelligence; 8/7/2025, Vol. 5 Issue 1, p1-30, 30p

Schlagwörter: KIDNEY stones, MACHINE learning, IMAGING systems, ARTIFICIAL intelligence, DIAGNOSIS, DEEP learning, URINARY organ diseases, RADIOGRAPHIC processing

Multi-behavior aware recommendation with joint contrastive learning and reinforced negative sampling.

Autoren: Du, Yujia Yu, Zhengtao Wang, Hongbin

Quelle: Complex & Intelligent Systems; Aug2025, Vol. 11 Issue 8, p1-17, 17p

A redundant weight removal method inspired by specific immunotherapy for boosting transfer learning security.

Autoren: Huang, Qing Deng, Hongli Wang, Junxiang et al.

Quelle: Complex & Intelligent Systems; Aug2025, Vol. 11 Issue 8, p1-27, 27p

Speech emotion recognition based on a stacked autoencoders optimized by PSO based grass fibrous root optimization.

Autoren: Zeng, Chi Li, Jialing Habibi, Abbas

Quelle: Scientific Reports; 7/18/2025, Vol. 15 Issue 1, p1-16, 16p

Schlagwörter: EMOTION recognition, PARTICLE swarm optimization, COMPUTER performance, OPTIMIZATION algorithms, DEEP learning, FEATURE extraction, AUTOENCODERS

Two-layer energy scheduling of electrical and thermal smart grids with energy hubs including renewable and storage units considering energy markets.

Autoren: Aich, Walid Basem, Ali Sawaran Singh, Narinderjit Singh et al.

Quelle: Scientific Reports; 7/11/2025, Vol. 15 Issue 1, p1-20, 20p

Schlagwörter: ENERGY management, SMART power grids, MATHEMATICAL programming, BILEVEL programming, COST effectiveness, ENERGY industries, RENEWABLE energy sources

A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training.

Autoren: Mao, Limin Shi, Hangming Chou, Yongxin et al.

Quelle: Complex & Intelligent Systems; Jul2025, Vol. 11 Issue 7, p1-22, 22p

Fine-grained entity disambiguation through numeric pattern awareness in transformer models.

Autoren: Jang, Jaeeun Kim, Sangmin Moon, Howon et al.

Quelle: Complex & Intelligent Systems; Jul2025, Vol. 11 Issue 7, p1-21, 21p

A fake news detection model using the integration of multimodal attention mechanism and residual convolutional network.

Autoren: Lu, Ying Yao, Naiwei

Quelle: Scientific Reports; 7/1/2025, Vol. 15 Issue 1, p1-15, 15p

Schlagwörter: DEEP learning, DATA fusion (Statistics), MISINFORMATION, RESEARCH evaluation, MULTIMODAL user interfaces

A hybrid slime mould algorithm with Levy Flight based mutation for malaria parasite detection.

Autoren: Conteh, Ibrahim Musa Abdulsalami, Aminu Onimisi Njai, Gibril et al.

Quelle: Multiscale & Multidisciplinary Modeling, Experiments & Design; Jun2025, Vol. 8 Issue 6, p1-32, 32p

A deep learning approach for accurate COVID-19 diagnosis from x-ray images using OBLMPA.

Autoren: Li, Xiaohua Fu, Shuai

Quelle: AIP Advances; Jun2025, Vol. 15 Issue 6, p1-13, 13p

Schlagwörter: CONVOLUTIONAL neural networks, SARS-CoV-2, DEEP learning, COMMON cold, X-ray imaging

Effective defense against physically embedded backdoor attacks via clustering-based filtering.

Autoren: Kutbi, Mohammed

Quelle: Complex & Intelligent Systems; Jun2025, Vol. 11 Issue 6, p1-12, 12p

Schlagwörter: MACHINE learning, ARTIFICIAL intelligence, IMAGE recognition (Computer vision), GAUSSIAN mixture models, DEEP learning

Hierarchical reinforcement learning based on macro actions.

Autoren: Jiang, Hao Wang, Gongju Li, Shengze et al.

Quelle: Complex & Intelligent Systems; Jun2025, Vol. 11 Issue 6, p1-17, 17p

Incorporating echo state network and sand cat swarm optimization algorithm based on quantum for named entity recognition.

Autoren: Huang, Fang Wang, Baocheng Safarzadeh, Jafar

Quelle: Scientific Reports; 5/29/2025, Vol. 15 Issue 1, p1-18, 18p

Schlagwörter: OPTIMIZATION algorithms, KNOWLEDGE graphs, ARTIFICIAL intelligence, IMAGE processing, INFORMATION retrieval, NATURAL language processing