Results 171 to 180 of about 476,390 (273)

Semantic network analysis of vaccine sentiment in online social media. [PDF]

Vaccine, 2017
Kang GJ, Ewing-Nelson SR, Mackey L, Schlitt JT, Marathe A, Abbas KM, Swarup S.   +6 more
europepmc   +1 more source

Multitarget Recognition of Flower Images Based on Lightweight Deep Neural Network and Transfer Learning

Advanced Intelligent Systems, EarlyView.
This article proposes a lightweight YOLOv4‐based detection model using MobileNetV3 or CSPDarknet53_tiny, achieving 30+ FPS and higher mAP. It also presents a ShuffleNet‐based classification model with transfer learning and GAN‐augmented images, improving generalization and accuracy.
Qingyang Liu, Yanrong Hu, Hongjiu Liu
wiley   +1 more source

Semantic Network Analysis Reveals Opposing Online Representations of the Search Term "GMO". [PDF]

Glob Chall, 2018
Jiang K, Anderton BN, Ronald PC, Barnett GA.   +3 more
europepmc   +1 more source

Edge Information‐Augmented Auxiliary Diagnosis Method for Cervical Cancer in Medical Decision‐Making Systems

Advanced Intelligent Systems, EarlyView.
To address the problems of insufficient utilization of multiscale features and inefficient feature sharing between tasks in the model, this study proposes an edge‐enhanced intelligent cervical cancer screening method that achieves feature reuse and improves efficiency by jointly optimizing nucleolus segmentation and lesion classification.
Li Wen, Xiaoqing Zhang, Tingyi Dai, Fangfang Gou, Jia Wu   +4 more
wiley   +1 more source

Editorial: Network analysis of social media texts

Frontiers in Research Metrics and Analytics
Ke Jiang, Weiai (Wayne) Xu, James Danowski   +2 more
doaj   +1 more source

Hierarchical Language Models for Semantic Navigation and Manipulation in an Aerial‐Ground Robotic System

Advanced Intelligent Systems, EarlyView.
A hierarchical multimodal framework coupling a large language model for task decomposition and semantic mapping with a fine‐tuned vision‐language model for semantic perception, enhanced by GridMask, is presented. An aerial‐ground robot team exploits the semantic map for global and local planning.
Haokun Liu, Zhaoqi Ma, Yunong Li, Junichiro Sugihara, Yicheng Chen, Jinjie Li, Moju Zhao   +6 more
wiley   +1 more source

Characteristics, Management, and Utilization of Muscles in Musculoskeletal Humanoids: Empirical Study on Kengoro and Musashi

Advanced Intelligent Systems, EarlyView.
Musculoskeletal humanoids exhibit rich biomechanical properties that remain insufficiently unified in prior discussions. This article systematically categorizes muscle characteristics into five properties: redundancy, independency, anisotropy, variable moment arm, and nonlinear elasticity, and analyzes their combined effects on control.
Kento Kawaharazuka, Kei Okada, Masayuki Inaba   +2 more
wiley   +1 more source

A Generalizable Transformer Framework for Gene Regulatory Network Inference from Single‐Cell Transcriptomes

Advanced Intelligent Systems, EarlyView.
FTGRN introduces an LLM‐enhanced framework for gene regulatory network inference through a two‐stage workflow. It combines a Transformer‐based model, pretrained on GPT‐4 derived gene embeddings and regulatory knowledge, with a fine‐tuning stage utilizing single‐cell RNA‐seq data.
Guangzheng Weng, Hyobin Kim, Patrick Martin, Junil Kim, Tae‐Hyung Kim, Gi‐Hoon Nam, Dongha Kim, Kyoung Jae Won   +7 more
wiley   +1 more source

Multivariate Contrastive Predictive Coding with Sliding Windows for Disease Prediction from Electronic Health Records

Advanced Intelligent Systems, EarlyView.
Adaptive multi‐indicator contrastive predictive coding is introduced as a self‐supervised pretraining framework for multivariate EHR time series. An adaptive sliding‐window algorithm and 2D convolutional neural network encoder capture localized temporal patterns and global indicator dependencies, enabling label‐efficient disease prediction that ...
Hongxu Yuan, Xiaozhu Jing, Yuzheng Yan, Wuman Luo   +3 more
wiley   +1 more source

Robust Dysarthric Speech Recognition with GAN Enhancement and LLM Correction

Advanced Intelligent Systems, EarlyView.
This study tackles dysarthric speech recognition by combining generative adversarial network (GAN)‐generated synthetic data with large language model (LLM)‐based error correction. The approach integrates three key elements: an improved CycleGAN to generate synthetic dysarthric speech for data augmentation, a multimodal automatic speech recognition core
Yibo He, Kah Phooi Seng, Chee Shen Lim, Li Minn Ang   +3 more
wiley   +1 more source