Results 91 to 100 of about 968,733 (291)

Conserved binding mode but diverse interfaces of MreC‐PBP2 interactions

FEBS Letters, EarlyView.
The crystal structure of abMreC reveals a conserved two β‐barrel architecture and provides structural insights into its role within the bacterial elongasome. The abMreC–abPBP2 complex model identifies the molecular basis of MreC‐mediated PBP2 recognition, contributing to the regulation of peptidoglycan synthesis.
Hyunseok Jang, Hyo Been Jin, Chang Min Kim, So Yeon Lee, Hyun Ho Park   +4 more
wiley   +1 more source

Training Fully Convolutional Neural Networks for Lightweight, Non-Critical Instance Segmentation Applications

Applied Sciences
Augmented reality applications involving human interaction with virtual objects often rely on segmentation-based hand detection techniques. Semantic segmentation can then be enhanced with instance-specific information to model complex interactions ...
Miguel Veganzones, Ana Cisnal, Eusebio de la Fuente, Juan Carlos Fraile   +3 more
doaj   +1 more source

PoSeg: Pose-Aware Refinement Network for Human Instance Segmentation

IEEE Access, 2020
Human instance segmentation is a core problem for human-centric scene understanding and segmenting human instances poses a unique challenge to vision systems due to large intra-class variations in both appearance and shape, and complicated occlusion ...
Desen Zhou, Qian He
doaj   +1 more source

Microbiome‐blood–brain barrier interactions in aging — mechanisms and therapeutic potential

FEBS Letters, EarlyView.
Aging reshapes the gut microbiome (↓SCFA‐producing commensals; ↑pro‐inflammatory outputs), shifting circulating metabolites (↓SCFAs; ↑LPS, ↑TMAO, ↑PAA) that act at the BBB to increase nonspecific transcytosis, alter transport, and promote astrocyte reactivity, heightening brain vulnerability.
Daniel Cuervo‐Zanatta, Hari Baskar Balasubramanian, Amir Pasokh, Marietta Zille   +3 more
wiley   +1 more source

Synthetic Instance Segmentation from Semantic Image Segmentation Masks [PDF]

In recent years, instance segmentation has garnered significant attention across various applications. However, training a fully-supervised instance segmentation model requires costly both instance-level and pixel-level annotations.
Shen, Yuchen, Zhang, Dong, Fu, Liyong, Zhang, Zhao, Ye, Qiaolin   +4 more
core   +1 more source

Underwater instance segmentation: a method based on channel spatial cross-cooperative attention mechanism and feature prior fusion

Frontiers in Marine Science
In aquaculture, underwater instance segmentation methods offer precise individual identification and counting capabilities. However, due to the inherent unique optical characteristics and high noise in underwater imagery, existing underwater instance ...
Zhiqian He, Lijie Cao, Lijie Cao, Xiaoqing Xu, Jianhao Xu   +4 more
doaj   +1 more source

Structure‐forward targeting of claudins with synthetic binders

FEBS Letters, EarlyView.
Claudins form the paracellular barriers between epithelial and endothelial tissues at tight junctions and are targets for molecular binders with the goal of modulating barrier permeability. Claudin‐binding molecules are relevant in drug delivery or in altering claudin interactions with disease‐causing proteins.
Alex J. Vecchio
wiley   +1 more source

A Unified Deep Architecture for Segmentation in Remote Sensing Images

Applied Computational Intelligence and Soft Computing
Deep learning–based segmentation models have gained significant focus in various computer vision applications, including remote sensing and medical imaging.
Nagamani Gonthina, L. V. Narasimha Prasad   +1 more
doaj   +1 more source

Nutrient/TOR signaling controls adipose mitochondrial transcription factor A (TFAM) to regulate organismal growth in Drosophila

FEBS Letters, EarlyView.
Animals must match their growth rate to available nutrients. We show that in Drosophila larvae, the nutrient‐sensing TOR kinase controls growth by regulating levels of TFAM, a key regulator of mitochondrial function, in the adipose tissue. When nutrients are abundant, high TOR activity suppresses TFAM, lowering mitochondrial bioenergetic activity and ...
Shrivani Sriskanthadevan‐Pirahas, Shahoon Khan, Abhishek Sharma, Byoungchun Lee, Savraj S. Grewal   +4 more
wiley   +1 more source

Machine Learning for Instance Segmentation [PDF]

, 2020
Volumetric Electron Microscopy images can be used for connectomics, the study of brain connectivity at the cellular level. A prerequisite for this inquiry is the automatic identification of neural cells, which requires machine learning algorithms and in particular efficient image segmentation algorithms. In this thesis, we develop new algorithms for
openaire   +2 more sources