Results 141 to 150 of about 5,528,069 (258)

Convolutional neural network for image processing

, 2015
Goal of this Diploma thesis was Convolutional neural network investigation in last years. Diploma thesis also contains information about designing of appropriate Convolutional neural network models and implementation of these models in Java programming ...
Krajčovičová, Mária
core  

BraMARS: An Interpretable Histopathology‐Driven Deep Learning Model for Brain Metastasis Risk Stratification in Surgically Resected Limited‐Stage SCLC

Advanced Science, EarlyView.
This study presents BraMARS, an explainable deep learning model that estimates future brain metastasis risk in surgically resected limited‐stage small‐cell lung cancer using routine H&E‐stained whole‐slide images. By linking model‐attributed spatial histopathology with clinical outcomes and proteomic programs, BraMARS provides a biologically ...
Zijian Yang, Taolue Wang, Shilong Liu, Zicheng Zhang, Yibo Zhang, Fan Yang, Bo Yu, Shuaishuai Gao, Yu Chen, Lin Yang, Meng Zhou   +10 more
wiley   +1 more source

Neuromorphic Optical Tracking and Imaging of Randomly Moving Targets Through Dynamic Dense Scattering Media

Advanced Science, EarlyView.
Vision begins not with images but with change: the retina fires only when something moves, handing the brain a stream of spikes. A neuromorphic imaging system adopts the same strategy—an event sensor that sees like the retina, a spiking network that thinks like the brain—to track and reconstruct fully randomly moving targets through tissue (phantom ...
Ning Zhang, Arto Nurmikko
wiley   +1 more source

Neuromorphic Devices and Computing for Sensing, Memory, and Control

Advanced Science, EarlyView.
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu, Nicholas Schaffer, Xiao Yang   +2 more
wiley   +1 more source

Automated measurement of Little's Irregularity Index on intraoral photographs using a convolutional neural network. [PDF]

BMC Oral Health
Kanemeier M, Ergün T, Stamm T, Middelberg C, Schmid JQ.   +4 more
europepmc   +1 more source

Analog Synaptic Plasticity in 2D Layered Material Iontronic Memtransistors for Brain‐Inspired Computing

Advanced Science, EarlyView.
In this work, we demonstrated a robust 2D MoS2 based iontronic memtransistor of planar architecture operated under the influence of an electrical double layer with versatile performance and applications, including pinched hysteresis nature of transfer curve, analogue channel conductance tuning, low‐voltage operation, logic‐gate operation, classical ...
Puranjay Saha, Saptarshi Bej, Bikas C. Das   +2 more
wiley   +1 more source

Assessment of Convolutional Neural Network and Vision Transformer Architectures for Structural Surface Classification. [PDF]

J Imaging
Thango BA, Thango SG.
europepmc   +1 more source

Multi‐Omics Integration Identifies a CDH3‐Associated Malignant Epithelial State and Immunosuppressive Niche to Predict Prognosis in Thymic Epithelial Tumors

Advanced Science, EarlyView.
Single‐cell, spatial, molecular, and pathology analyses identify a CDH3‐associated malignant epithelial state in thymic epithelial tumors. This state links stem‐like and EMT programs to M2 macrophage–rich immunosuppressive niches, genomic instability, poor survival, and drug vulnerability.
Yuntao Feng, Jingyu Chen, Lang Xia, Tao Wang, Yuzhou Wang, Lei Zhang, Guofang Zhao, Long Xu, Juemin Yu, Yunlang She, Junqi Wu, Yue Zhao, Chang Chen, Deping Zhao   +13 more
wiley   +1 more source

Deep Learning-Based Classification of Melanoma Using Dermoscopic Images: Comparative Evaluation of Convolutional Neural Network and DenseNet Models. [PDF]

JMIR Dermatol
Sanghvi H, Agritis A, Alvarez I, Patel M, Wang S, Patel R, Banoub R, Makkar T.   +7 more
europepmc   +1 more source

Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes

Advanced Science, EarlyView.
StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley   +1 more source