Results 131 to 140 of about 4,047,749 (292)

NICE: A Two‐Step Non‐Invasive Framework for Embryo cfDNA Read Enrichment and Quality Assessment

Advanced Science, EarlyView.
The non‐invasive NICE framework, built on an ensemble stacking machine learning model, prioritizes embryos by analyzing cell‐free DNA from spent culture medium. By integrating multimodal signals, including genomic and epigenetic profiles, this automated approach standardizes morphological assessment without human bias, paving the way for more precise ...
Xueya Zhou, Shu Ding, Zhenyi Zhang, Qiaoling Shangguan, Jie Qiao, Peijie Zhou, Yidong Chen   +6 more
wiley   +1 more source

Deep Learning and Convolutional Neural Networks (CNNs)

Deep Learning (DL), a subfield of Artificial Intelligence (AI) and Machine Learning (ML), has revolutionized computational intelligence by enabling machines to automatically learn hierarchical representations from large datasets. Among the various deep learning architectures, Convolutional Neural Networks have emerged as a dominant framework ...
V. V. Virginia, U.M. Mbanaso, E.S. Chaku, I.O. Clementina, Gilbert Aimufua   +4 more
openaire   +1 more source

Food Image Recognition by Using Convolutional Neural Networks (CNNs)

CoRR, 2016
Food image recognition is one of the promising applications of visual object recognition in computer vision. In this study, a small-scale dataset consisting of 5822 images of ten categories and a five-layer CNN was constructed to recognize these images.
openaire   +2 more sources

Integrating convolutional neural networks into a sparse distributed representation model based on mammalian cortical learning

, 2016
Biological brains exhibit a remarkable capacity to recognise real-world patterns effectively. Despite major advances in neuroscience over the last few decades, an understanding of the brain's underlying mechanisms for pattern recognition remains ...
Daniel E. Padilla, McDonnell, M.D., Mark D. McDonnell, Padilla, D.E.   +3 more
core   +1 more source

A Unified Hierarchical Multiscale Fusion Framework for Drug–Target Affinity Prediction: From Benchmark Performance to Nanomolar Inhibitor Discovery

Advanced Science, EarlyView.
A multimodal fusion framework integrating sequence, atomic, and fragment representations captures drug–target interactions across multiple scales. The model delivers strong predictive performance and enables efficient virtual screening. Applied to hematopoietic progenitor kinase 1 (HPK1), it identifies structurally diverse inhibitors with nanomolar ...
Shuo Liu, Xiang Zhang, Haixia Feng, Yuquan Li, Xiaoqing Gong, Yong Liang, Xiaojun Yao, Huanxiang Liu   +7 more
wiley   +1 more source

AI‐Assisted Tumor Boundary Delineation via Targeted Ultrasmall Iron Oxide Nanoprobe for High‐Contrast HER2‐Positive Tumor Imaging

Advanced Science, EarlyView.
A novel targeted and pH‐responsive MRI contrast agent was integrated with a 3D nnU‐Net deep learning framework to enable accurate delineation of tumor boundary morphology in HER2‐positive breast cancer imaging. ABSTRACT Breast cancer continues to be a leading cause of cancer‐related mortality in women globally, where precise diagnosis and clear tumor ...
Jiaying Zheng, Yi Zhu, Xinrui Li, Sunxian Dai, Xiangyuan Ma, Hongwei Lu, Zhongling Wang, Benqing Zhou   +7 more
wiley   +1 more source

Recognizing Events in Videos Using Deep Learning Techniques

Syrian Journal for Science and Innovation
Neural network models have revolutionized action recognition in videos, enabling precise and efficient processing of complex visual data. These AI-powered tools mimic or even surpass human abilities in understanding visual information.
Waseem Safi, Hisham Muawen
doaj   +1 more source

Low Latency Global Carbon Budget Reveals Late 2024 Carbon Losses and Contrasting Early 2025 Land Sink Recovery Signals

Advanced Science, EarlyView.
Low latency carbon budget estimates for July 2024–June 2025 combine atmospheric CO2 growth rates, fossil emissions, ocean uptake, DGVM land fluxes, and OCO‐2 inversions. The budget shows that late‐2024 land carbon losses dominate the annual anomaly, while early‐2025 recovery differs between bottom‐up models and top‐down inversions, especially in ...
Piyu Ke, Philippe Ciais, Yitong Yao, Stephen Sitch, Wei Li, Xiaomeng Du, Xiaofan Gui, Ben Poulter, Thomas Colligan, Auke M. van der Woude, Joram Hooghiem, Wouter Peters, Zhu Liu, Zhu Deng, Zhe Jin, Xiangjun Tian, Yilong Wang, Junjie Liu, Sudhanshu Pandey, Chris O'Dell, Jiang Bian, John Miller, Xin Lan, Jefferson Goncalves De Souza, Michael O'Sullivan, Pierre Friedlingstein, Julien Alléon, Yi Xi, Daniel S. Goll, Lei Zhu, Guido R. van der Werf, Shilong Piao, Frédéric Chevallier   +32 more
wiley   +1 more source

Additive Manufacturing of High‐Performance Polymers for Extreme Environments

Advanced Science, EarlyView.
Additive manufacturing of high‐performance polymers for extreme environments is critically reviewed through an integrated chemistry‐processing‐structure‐property‐qualification framework. The review compares fused filament fabrication, selective laser sintering, and direct ink writing, linking rheology and thermal history to crystallization, defect ...
Md Tofazzal Hossain, Mohammed Intishar Nur, Md Shajedul Hoque Thakur, Indranil Dey, Md Mesbahul Maruf, Md Jahid Hasan, Suryasarathi Bose, Muhammad M. Rahman   +7 more
wiley   +1 more source

Deep‐Learning‐Based Denoising for Improved Phase Precision in Electron Holography of Electromagnetic Fields in Nanoscale Materials

Advanced Science, EarlyView.
Low‐dose electron holography is limited by shot noise, which buries weak phase signals. HoloDenoiser, a physics‐informed network that works simultaneously in the spatial and frequency domains, locates and protects the holographic sideband while suppressing noise in the hologram.
Ye Luo, Luyang Wang, Zhiling Yu, Xiaowen Chen, Xiaoyu Wang, Ya‐Hui Jia, Thibaud Denneulin, Yu Han, Rafal E. Dunin‐Borkowski, Fengshan Zheng, Qi Liu   +10 more
wiley   +1 more source