Suchergebnisse - multi-modal coding–decoding process*

MDLFormer: multi-modal global context-based swin transformer for image manipulation detection and localization.

Autoren: Thakur, Rahul Rohilla, Rajesh

Quelle: Signal, Image & Video Processing; Nov2025, Vol. 19 Issue 11, p1-8, 8p

Research on Soil Pore Segmentation of CT Images Based on MMLFR-UNet Hybrid Network.

Autoren: Qin, Changfeng Zhang, Jie Duan, Yu et al.

Quelle: Agronomy; May2025, Vol. 15 Issue 5, p1170, 19p

Schlagwörter: COMPUTED tomography, POROSITY, NUTRIENT cycles, ENVIRONMENTAL soil science, IMAGE segmentation

Booming far: the long-range vocal strategy of a lekking bird

Autoren: C. Cornec Y. Hingrat T. Aubin et al.

Quelle: Royal Society Open Science, Vol 4, Iss 8 (2017)

Schlagwörter: exploded lek, houbara bustard, low-frequency vocalization, male–male competition, multi-modal coding–decoding process, redundancy, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2054-5703

Zugangs-URL: https://doaj.org/article/29f1b6a552724c5c8746d31da60ecefa

Table S1-S6 and Figure S1-S2 from Booming far: the long-range vocal strategy of a lekking bird

Autoren: C. Cornec Y. Hingrat T. Aubin et al.

Schlagwörter: Animal Behaviour, exploded lek, houbara bustard, low-frequency vocalization, male–male competition, multi-modal coding–decoding process, redundancy

Verfügbarkeit: https://doi.org/10.6084/m9.figshare.5281216.v1
https://figshare.com/articles/journal_contribution/Table_S1-S6_and_Figure_S1-S2_from_Booming_far_the_long-range_vocal_strategy_of_a_lekking_bird/5281216

Multi-label remote sensing classification with self-supervised gated multi-modal transformers.

Autoren: Liu, Na Yuan, Ye Wu, Guodong et al.

Quelle: Frontiers in Computational Neuroscience; 2025, p1-15, 15p

Schlagwörter: REMOTE sensing, MULTISENSOR data fusion, MULTISPECTRAL imaging, TRANSFORMER models, CLASSIFICATION, SUPERVISED learning, SYNTHETIC aperture radar

Dual-Branch Cross-Fusion Normalizing Flow for RGB-D Track Anomaly Detection.

Autoren: Gao, Xiaorong Wen, Pengxu Li, Jinlong et al.

Quelle: Sensors (14248220); Apr2025, Vol. 25 Issue 8, p2631, 14p

Schlagwörter: ANOMALY detection (Computer security), DEPTH maps (Digital image processing), COMPUTER vision, TRACK & field, PRIOR learning

Set‐membership state estimation for complex networks with chance constraints under multi‐modal deception attacks.

Autoren: Shi, Miaomiao Hu, Chen Guo, Jian et al.

Quelle: Asian Journal of Control; Jul2025, Vol. 27 Issue 4, p1854-1865, 12p

Schlagwörter: MATRIX inequalities, MATHEMATICAL optimization, DECEPTION, CYBERTERRORISM, COMPUTER simulation

Multi-label remote sensing classification with self-supervised gated multi-modal transformers.

Autoren: Na Liu Ye Yuan Guodong Wu et al.

Quelle: Frontiers in Computational Neuroscience; 2024, p1-15, 15p

Schlagwörter: TRANSFORMER models, SYNTHETIC aperture radar, REMOTE sensing, MULTISENSOR data fusion, RESEARCH personnel

EDET: Entity Descriptor Encoder of Transformer for Multi-Modal Knowledge Graph in Scene Parsing.

Autoren: Ma, Sai Wan, Weibing Yu, Zedong et al.

Quelle: Applied Sciences (2076-3417); Jun2023, Vol. 13 Issue 12, p7115, 20p

Schlagwörter: KNOWLEDGE graphs, KNOWLEDGE representation (Information theory), EXPERIMENTAL design, MODEL validation

A multi-modal fusion framework for continuous sign language recognition based on multi-layer self-attention mechanism.

Autoren: Xue, Cuihong Yu, Ming Yan, Gang et al.

Quelle: Journal of Intelligent & Fuzzy Systems; 2022, Vol. 43 Issue 4, p4303-4316, 14p

Schlagwörter: SIGN language, CONVOLUTIONAL neural networks, TEXT recognition, OPTICAL flow, STREAMFLOW, FEATURE extraction

Multimodal Seed Data Augmentation for Low-Resource Audio Latin Cuengh Language.

Autoren: Jiang, Lanlan Qin, Xingguo Zhang, Jingwei et al.

Quelle: Applied Sciences (2076-3417); Oct2024, Vol. 14 Issue 20, p9533, 13p

Schlagwörter: DATA augmentation, PROCESS capability, LATIN language, SPEECH, CHINESE language

Structured light meets machine intelligence.

Autoren: Zhang, Zilong Kong, Lingyu Zhang, Lianghaoyue et al.

Quelle: eLight; 9/29/2025, Vol. 5 Issue 1, p1-35, 35p

Schlagwörter: ARTIFICIAL intelligence, OPTICAL devices, DETECTION algorithms, QUANTUM theory, IMAGING systems

Personalized learning path planning for higher education based on deep generative models and quantum machine learning: a multimodal learning analysis method integrating transformer, adversarial training and quantum state classification.

Autoren: Sun, Changzhi Huang, Shijie Sun, Banghui et al.

Quelle: Discover Artificial Intelligence; 3/26/2025, Vol. 5 Issue 1, p1-19, 19p

Schlagwörter: HIGHER education, TRANSFORMER models, DATA integration, QUANTUM states, INDIVIDUALIZED instruction, PROBABILISTIC generative models, MACHINE learning, QUANTUM information science

MAT-PointPillars: Enhanced PointPillars algorithm based on multi-scale attention mechanisms and transformer.

Autoren: Yao, Xinpeng Liu, Peiyuan Zhou, Jingmei et al.

Quelle: PLoS ONE; 6/27/2025, Vol. 20 Issue 6, p1-16, 16p

Schlagwörter: DETECTION algorithms, OBJECT recognition (Computer vision), TRANSFORMER models, POINT cloud, ALGORITHMS

Glioma segmentation of optimized 3D U-net and prediction of multi-modal survival time.

Autoren: Liu, Qihong Liu, Kai Bolufé-Röhler, Antonio et al.

Quelle: Neural Computing & Applications; Jan2022, Vol. 34 Issue 1, p211-225, 15p

Schlagwörter: GLIOMAS, SURVIVAL analysis (Biometry), DEEP learning, MACHINE learning, DIAGNOSIS, MEDICAL technology, RADIOLOGIC technology

DIGITAL TECHNOLOGIES AND ARTIFICIAL INTELLIGENCE IN THE MULTIMODAL DESIGN OF SIGN LANGUAGE EDUCATION.

Autoren: Georgieva, Diyana Tsankov, Nikolay

Quelle: Strategies for Policy in Science & Education / Strategii na Obrazovatelnata i Nauchnata Politika; 2025, Vol. 33 Issue 2, p155-171, 17p

Schlagwörter: DIGITAL technology, ARTIFICIAL intelligence, SIGN language, DEAF people, NATURAL languages, DEAF children

Convolutional neural network (CNN) configuration using a learning automaton model for neonatal brain image segmentation.

Autoren: Sarafraz, Iran Agahi, Hamed Mahmoodzadeh, Azar

Quelle: PLoS ONE; 1/17/2025, Vol. 20 Issue 1, p1-16, 16p

Schlagwörter: CONVOLUTIONAL neural networks, MAGNETIC resonance imaging, BRAIN imaging, DATABASES, INFANTS, REINFORCEMENT learning

A Semantic Segmentation Method for Road Scene Images Based on Improved DeeplabV3+ Network.

Autoren: Lihua Bi Xiangfei Zhang Shihao Li et al.

Quelle: International Journal of Advanced Computer Science & Applications; Aug2024, Vol. 15 Issue 8, p841-849, 9p

YOLOv8-RBean: Runner Bean Leaf Disease Detection Model Based on YOLOv8.

Autoren: Chen, Hongbing Zhai, Haoting Hu, Jinghuan et al.

Quelle: Agronomy; Apr2025, Vol. 15 Issue 4, p944, 22p

Schlagwörter: OBJECT recognition (Computer vision), FEATURE extraction, SMART structures, VIRUS diseases, FOOD security

Semantic Segmentation Method of Residential Areas in Remote Sensing Images Based on Cross-Attention Mechanism.

Autoren: Zhao, Bin Mi, Yang Sun, Ruohuai et al.

Quelle: Remote Sensing; Sep2025, Vol. 17 Issue 18, p3253, 25p

Schlagwörter: REMOTE sensing, RESIDENTIAL areas, IMAGE segmentation, APPLIED sciences, FEATURE extraction, GENERALIZATION