Results 151 to 160 of about 220,610 (290)
This paper presents a degeneracy‐aware light detection and ranging (LiDAR)‐inertial framework that enhances LiDAR simultaneous localization and mapping performance in challenging environments. The proposed system integrates a dual‐layer robust odometry frontend with a Scan‐Context‐based loop‐closure detection backend.
Haoming Yang +4 more
wiley +1 more source
A painting art rendering system by deep learning framework and machine translation. [PDF]
Wang S, Shahir S, Ismail MU.
europepmc +1 more source
On Formal Analysis of OO Languages using Rewriting Logic: Designing for Performance [PDF]
A. Farzan +14 more
core +1 more source
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 +7 more
wiley +1 more source
An interpretable model based on concept and argumentation for tabular data. [PDF]
Chi H, Wang D, Liao B, Cui G, Mao F.
europepmc +1 more source
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 +3 more
wiley +1 more source
H3-MOSAIC: multimodal generative AI for semantic place detection from high-frequency GPS on H3 grids in mental health geomatics. [PDF]
Liu L +6 more
europepmc +1 more source
Linguistic Mistakes and Semantic Rules
Abstract This paper critically examines the idea that language use is governed by semantic rules. In the literature, two competing rules have been proposed: the truth rule and the rule of use. The truth rule requires speakers to always use expressions truthfully, while the rule of use requires speakers to use expressions in accordance ...
openaire +1 more source
Robust Dysarthric Speech Recognition with GAN Enhancement and LLM Correction
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 +3 more
wiley +1 more source
ROS 2-Based Architecture for Autonomous Driving Systems: Design and Implementation. [PDF]
Bonci A +5 more
europepmc +1 more source

