Results 91 to 100 of about 193,972 (282)

Weakly Supervised Deep Semantic Segmentation Using CNN and ELM with Semantic Candidate Regions

Complexity, 2019
The task of semantic segmentation is to obtain strong pixel-level annotations for each pixel in the image. For fully supervised semantic segmentation, the task is achieved by a segmentation model trained using pixel-level annotations.
Xinying Xu, Guiqing Li, Gang Xie, Jinchang Ren, Xinlin Xie   +4 more
doaj   +1 more source

Semantic-Segmentation-Suite

, 2020
Acknowledge: this is original code in the github page. The link is https://guides.github.com/activities/citable-code/.
openaire   +1 more source

A Wireless, Battery‐Free Artificial Throat Patch with Deep Learning for Emotional Speech Recognition

Advanced Science, EarlyView.
In this work, Xu and co‐workers develop a wireless, battery‐free artificial throat patch system (ATPS) consisting of a carbon nanotube‐based thin‐film strain sensor and a miniaturized flexible printed circuit board, to enable real‐time sensing of throat signals.
Bingxin Xu, Guanming Lin, Xiaohui Hong, Chuting Liu, Xinyi Qu, Kangjian Jiao, Lei Zhang, Bingzhe Xu, Jun Yan, Yancong Qiao, Xudong Lin   +10 more
wiley   +1 more source

Multimodal Cross‐Attentive Graph‐Based Framework for Predicting In Vivo Endocrine Disruptors

Advanced Science, EarlyView.
A multimodal cross‐attentive graph neural network integrates molecular graphs with androgen and estrogen adverse outcome pathway (AOP)–anchored in vitro assay signals to predict in vivo endocrine disruption. By fusing information on Tier‐1 AOP logits with chemical structures, the framework achieves high accuracy and provides assay‐traceable ...
Eder Soares de Almeida Santos, Gustavo Felizardo Santos Sandes, Artur Christian Garcia da Silva, Holli‐Joi Martin, Eugene N. Muratov, Rodolpho de Campos Braga, Bruno Junior Neves   +6 more
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

Multimodal AI‐Driven Identification of Dehydrocostus Lactone as a Potent Renal Fibrosis Attenuator Targeting IQGAP1

Advanced Science, EarlyView.
Renal fibrosis, a hallmark of CKD, lacks effective treatments. Herein, we developed a multimodal AI model (TCM‐SPred) to identify anti‐fibrotic agents and found that dehydrocostus lactone (DCL) targets IQGAP1 to inhibit Wnt signaling, blocking the interaction between IQGAP1 and CCT3, demonstrating potent anti‐fibrotic activity in vitro and in vivo ...
Weijiang Lin, Wenzhuo Xu, Kang Liu, Ping Wang, Zhenzhen Zhu, Wenyu Lu, Zhe Zheng, Xiaoqian Peng, Xunkai Yin, Shulan Mei, An Pan, Jian Liu, Lihong Hu   +12 more
wiley   +1 more source

MicrobeDiscover: A Knowledge Graph–Enabled AI Framework for Identifying Microbes for Inorganic Nanomaterial Biosynthesis

Advanced Science, EarlyView.
Microbial synthesis of nanomaterials (NMs) is eco‐friendly, but the screening of microorganisms is limited by inefficient traditional methods (currently only involving∽400 microorganisms/90 NMs). We propose AI framework MicrobeDiscover, integrating a knowledge graph of microbe‐NM interactions.
Ludi Wang, Hexing Han, Yufeng Liu, Zhiyuan Ning, Yujie Ma, Haidan Wang, Jinling Xu, Qiansheng Huang, Wenjuan Cui, Yuanchun Zhou, Yang Gao, Bin Wang, Yi Du   +12 more
wiley   +1 more source

Integrating Spatial Proteogenomics in Cancer Research

Advanced Science, EarlyView.
Xx xx. ABSTRACT Background: Spatial proteogenomics marks a paradigm shift in oncology by integrating molecular analysis with spatial information from both spatial proteomics and other data modalities (e.g., spatial transcriptomics), thereby unveiling tumor heterogeneity and dynamic changes in the microenvironment.
Yida Wang, Yang Wu, Feng Zhang, Parthiban Periasamy, Haiyue You, Denise Goh, Rachel Elizabeth Ann Fincham, Xin Ning, Danping Wu, Lu Liu, Ying Jiang, Zhiwen Qian, Joe Yeong, Yan Zhang   +13 more
wiley   +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

Automatically Defining Protein Words for Diverse Functional Predictions Based on Attention Analysis of a Protein Language Model

Advanced Science, EarlyView.
Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen, Jingrui Zhong, Xiaochun Zhang, Jingke Chen, Lin Guo, Xiaoliang Xiong, Xiaonan Zhang, Xiangyu Liu, Bailong Xiao, Boxue Tian   +9 more
wiley   +1 more source