Results 171 to 180 of about 2,563,053 (365)

Tumor Auxiliary Prediction Strategy Based on Multiscale Feature Fusion in Medical Decision‐Making System

Advanced Intelligent Systems, EarlyView.
GA: MCFFS method architecture. Pathological images are processed by the multi‐level feature information fusion (MLFF) method and the multi‐scale feature map fusion strategy to achieve the recognition result of cell nuclei. The MLFF module contains convolution blocks, spatial self‐attention, and atrous spatial pyramid pooling.
Yingqing Lu, Jing Zhou, Fangfang Gou, Jia Wu   +3 more
wiley   +1 more source

Large Language Model‐Embedded Intelligent Robotic Scrub Nurse with Multimodal Input for Enhancing Surgeon–Robot Interaction

Advanced Intelligent Systems, EarlyView.
A large language model (LLM)‐powered multimodal robotic scrub nurse control framework is proposed for enhancing human–robot interaction. Inside, the vision module gives out instrument class, location, and occlusion relationship. Speech module captures and converts user's speech commands.
Wing Yin Ng, Wanyu Ma, Pheng Ann Heng, Philip Wai Yan Chiu, Zheng Li   +4 more
wiley   +1 more source

Reliability of retrieval from semantic memory: Common categories [PDF]

, 1984
Francis S. Bellezza
openalex   +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

A contribution of Natural Language Processing to the study of semantic memory loss in patients with Alzheimer’s disease

Revista de Lenguas para Fines Específicos, 2017
This paper addresses semantic memory loss from the perspective of Natural Language Processing. Dementia disorders and, in particular, Alzheimer’s disease (AD) present a loss of cognitive functions, being one of them semantic memory impairment.
Beatriz Pérez Cabello de ALba
doaj  

Semantic cues, rhyme cues, and two varieties of recognition memory [PDF]

, 1993
David L. Horton, Timothy J. Pavlick
openalex   +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

Towards Avatars with Artificial Minds: Role of Semantic Memory [PDF]

, 2007
he first step towards creating avatars with human-like artificial minds is to give them human-like memory structures with an access to general knowledge about the world. This type of knowledge is stored in semantic memory.
Duch, Wlodzislaw, Sarnatowicz, Tomasz, Szymanski, Julian   +2 more
core  

Progressive Decline of Semantic Memory with Preservation of Number Processing and Calculation [PDF]

, 1993
Han Diesfeldt
openalex   +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