Results 181 to 190 of about 307,473 (285)

Semantic Mapping in ROS

, 2013
[CATALÀ] En el últims anys els robots estan més presents a la nostra vida quotidiana. Els podem trobar guiant gent a museus, ajudant a cirurgians durant operacions i també netejant cases autònomament. Amb l'objectiu de permetre als robots realitzar tasques humanes i cooperar amb persones, hem de proporcionar-los la capacitat d'entendre entorns humans i
openaire   +2 more sources

Interactive Prompt‐Guided Robotic Grasping for Arbitrary Objects Based on Promptable Segment Anything Model and Force‐Closure Analysis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu, Yaxin Liu, Ruiqing Han, Kai Zheng, Yufeng Yao, Ming Zhong   +5 more
wiley   +1 more source

Real-time semantic segmentation of driving scenes via effective attention-based information fusion and hybrid encoder. [PDF]

Sci Rep
Cărunta C, Cărunta A, Mizeranschi AE, Popa CA.   +3 more
europepmc   +1 more source

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

Hierarchical Compositional Alignment for Zero-Shot Part-Level Segmentation. [PDF]

Sensors (Basel)
Yang S, Ji S, Xiao Z, Liu X, Wei W.
europepmc   +1 more source

BMPCQA: Bioinspired Metaverse Point Cloud Quality Assessment Based on Large Multimodal Models

Advanced Intelligent Systems, EarlyView.
This study presents a bioinspired metaverse point cloud quality assessment metric, which simulates the human visual evaluation process to perform the point cloud quality assessment task. It first extracts rendering projection video features, normal image features, and point cloud patch features, which are then fed into a large multimodal model to ...
Huiyu Duan, Kang Fu, Sijing Wu, Yunhao Li, Zicheng Zhang, Qiang Hu, Xiongkuo Min, Guangtao Zhai   +7 more
wiley   +1 more source

ECAB-SegFormer: A Boundary-Aware and Efficient Channel Attention Network for <i>Ulva prolifera</i> Semantic Segmentation in Remote Sensing Imagery. [PDF]

Sensors (Basel)
Liang Y, Cao D, Ji Z, Yang H, Guo M, Liu X, Guo X, Wu J, Song Y, Zhang S.   +9 more
europepmc   +1 more source

VAE+DDPG: An Attention‐Enhanced Variational Autoencoder for Deep Reinforcement Learning‐Based Autonomous Navigation in Low‐Light Environments

Advanced Intelligent Systems, EarlyView.
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee, Chanhong Hwang, Hyunseok Kang, Yechan Park, Hangwoo Jin, Tuan Anh Nguyen, Eunmi Choi, Dugki Min   +7 more
wiley   +1 more source

Functional Specialization of the Visual Word Form Area During Word Reading: A Multimodal Neuroimaging Study. [PDF]

Neurobiol Lang (Camb)
Gu L, Li H, Qu J, Yang J, Fu X, Hu R, Mei L.   +6 more
europepmc   +1 more source

Context Awareness and Human–Robot Interaction Optimization for Museum Intelligent Guide Robot

Advanced Intelligent Systems, EarlyView.
This study presents a context‐aware human–robot interaction framework designed for intelligent museum guide robots. The system features a three‐layer architecture—perception, understanding, and behavior execution—that enables adaptive and meaningful interactions with museum visitors.
Anna Zou, Yue Meng, Shijing Tong
wiley   +1 more source