Results 101 to 110 of about 6,372,670 (283)

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

Anomaly Detection in Blockchain Networks Using Unsupervised Learning: A Survey

Algorithms
In decentralized systems, the quest for heightened security and integrity within blockchain networks becomes an issue. This survey investigates anomaly detection techniques in blockchain ecosystems through the lens of unsupervised learning, delving into ...
Christos Cholevas, Eftychia Angeli, Zacharoula Sereti, Emmanouil Mavrikos, George E. Tsekouras   +4 more
doaj   +1 more source

An Efficient Detection Platform Based on Mesoporous Au@Cr2O3 Particles with Schwarz P Surface for Precise Periodontitis Metabolite Profiling

Advanced Science, EarlyView.
A non‐invasive periodontitis diagnosis platform was developed using Au nanoparticles‐decorated mesoporous Cr2O3 (Au@mCr2O3) particles with Schwarz P surface as matrix for saliva metabolic fingerprinting (SMFs) analysis via MALDI‐MS. With the assistance of machine learning of SMFs, this platform enables efficient diagnosis and the screening of potential
Yue Sun, Yan Wang, Fangying Shi, Wenhe Xie, Yiding Zhang, Heyuhan Zhang, Chunhui Deng, Limin Wu, Meihua Chen, Yonghui Deng   +9 more
wiley   +1 more source

Cell Segmentation Without Annotation by Unsupervised Domain Adaptation Based on Cooperative Self-Learning

IEEE Access
Semantic cell segmentation from microscopic images is essential for the quantitative evaluation of cell morphology. Although supervised deep-learning-based models offer accurate segmentation, their performance degrades for unknown cell types.
Shintaro Miyaki, Takashi Morikura, Shori Nishimoto, Yuta Tokuoka, Takahiro G. Yamada, Akira Funahashi   +5 more
doaj   +1 more source

An online deep extreme learning machine based on forgetting mechanism

Dianzi Jishu Yingyong, 2018
The development of deep learning promotes the development of deep online learning, and online learning tends to have strong effectiveness. Based on the principle of online extreme learning machine and the principle of autoencoder of deep extreme learning
Liu Buzhong
doaj   +1 more source

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning [PDF]

, 2014
Automatic species classification of birds from their sound is a computational tool of increasing importance in ecology, conservation monitoring and vocal communication studies.
Plumbley, Mark D., Stowell, D, Plumbley, MD, Dan Stowell, Mark D. Plumbley, Stowell, Dan; id_orcid, Stowell, Dan   +6 more
core   +2 more sources

StackingNet: Collective Inference Across Independent AI Foundation Models

Advanced Science, EarlyView.
ABSTRACT Artificial intelligence (AI) built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems remain isolated and cannot readily share their capabilities. Coordinating the complementary strengths of independently developed, black‐box foundation models is essential for trustworthy ...
Siyang Li, Chenhao Liu, Dongrui Wu, Zhigang Zeng, Lieyun Ding   +4 more
wiley   +1 more source

When Low Rank Representation Based Hyperspectral Imagery Classification Meets Segmented Stacked Denoising Auto-Encoder Based Spatial-Spectral Feature

Remote Sensing, 2018
When confronted with limited labelled samples, most studies adopt an unsupervised feature learning scheme and incorporate the extracted features into a traditional classifier (e.g., support vector machine, SVM) to deal with hyperspectral imagery ...
Cong Wang, Lei Zhang, Wei Wei, Yanning Zhang   +3 more
doaj   +1 more source

Design and Engineering of an Artificial Bifunctional N‐Deacetylase/N‐Sulfotransferase for the Biosynthesis of N‐Sulfated Heparosan

Advanced Science, EarlyView.
An artificial bifunctional N‐deacetylase/N‐sulfotransferase was engineered in Escherichia coli by combining screened N‐deacetylases with an NST domain. The integrated engineering strategy improved enzyme performance. The optimized enzyme efficiently converted heparosan into N‐sulfated heparosan, addressing a key bottleneck in microbial heparin ...
Xintong Xi, Ruirui Xu, Daoan Wang, Guobin Yin, Xinjing Wang, Haiqin Chen, Guocheng Du, Jian Chen, Zhen Kang   +8 more
wiley   +1 more source