Results 111 to 120 of about 500,543 (293)

Spatial Proximity Relations-Driven Semantic Representation for Geospatial Entity Categories

ISPRS International Journal of Geo-Information
Unsupervised representation learning can train deep learning models to formally express the semantic connotations of objects in the case of unlabeled data, which can effectively realize the expression of the semantics of geospatial entity categories in ...
Yongbin Tan, Hong Wang, Rongfeng Cai, Lingling Gao, Zhonghai Yu, Xin Li   +5 more
doaj   +1 more source

Plaisir and jouissance. The case of potential and textual reading of Barthes’ theory [PDF]

, 2015
The article is an attempt of the analysis and the interpretation of the categories ‘pleasure’ (Fr. plaisir) and ‘delight’ (Fr. jouissance), in the context of philosophically oriented theoretical‑literary considerations of Roland Barthes, sacrificed to ...
Elżbieta, Kołdrzak
core   +1 more source

Design of Safe and Efficient Adenine Base Editors via Protein Language Model Screening for Osteoarthritis Treatment

Advanced Science, EarlyView.
ABSTRACT Base editors enable precise genome modification and have emerged as a promising therapeutic approach for correcting diseases caused by single‐nucleotide variants. While the current efficient version of adenine base editors (ABEs), such as ABE8e, exhibits exceptional efficiency for A‐to‐G conversions, their clinical translation is hindered by ...
Jiawei Yao, Dalin Chen, Ziyi Zhang, Jingxuan Ren, Chengcheng Zhao, Shengfang Wang, Mengyu Shang, Dawei Jiang, Yinuo Li, Su'an Tang, Kai Li, Xiaohui Zhang, Xiaogang Wang   +12 more
wiley   +1 more source

Redefining linguistic categories through network theory

Language and Cognition
Categorization is a dynamic cognitive process that organizes human knowledge. As such, categorization processes are integral of the linguistic system and are primarily manifested in the conceptual categories represented in semantic memory.
Natividad Hernández Muñoz, Carmela Tomé Cornejo, Miguel López   +2 more
doaj   +1 more source

Decoding Naturalistic Episodic Memory with Artificial Intelligence and Brain‐Machine Interface

Advanced Science, EarlyView.
Episodic memory weaves together what, where, and when of experience into a personal narrative. Cutting‐edge AI models may decode this intricate process in real‐life settings, revealing how neural activity encodes naturalistic memories. By merging AI with brain–machine interfaces, researchers are edging closer to mapping and even engineering memory ...
Dong Song
wiley   +1 more source

Learnable Diffusion Framework for Mouse V1 Neural Decoding

Advanced Science, EarlyView.
We introduce Sensorium‐Viz, a diffusion‐based framework for reconstructing high‐fidelity visual stimuli from mouse primary visual cortex activity. By integrating a novel spatial embedding module with a Diffusion Transformer (DiT) and a synthetic‐response augmentation strategy, our model outperforms state‐of‐the‐art fMRI‐based baselines, enabling robust
Kaiwen Deng, Peter S. Schwendeman, Yuanfang Guan   +2 more
wiley   +1 more source

Visual Categorization of Objects into Animal and Plant Classes Using Global Shape Descriptors

, 2019
How humans can distinguish between general categories of objects? Are the subcategories of living things visually distinctive? In a number of semantic-category deficits, patients are good at making broad categorization but are unable to remember fine and
Sadeghi, Zahra
core  

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Thematically Reinforced Explicit Semantic Analysis

, 2013
We present an extended, thematically reinforced version of Gabrilovich and Markovitch's Explicit Semantic Analysis (ESA), where we obtain thematic information through the category structure of Wikipedia.
Haralambous, Yannis, Klyuev, Vitaly
core   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source