Results 211 to 220 of about 324,009 (309)

Advances in functional magnetic resonance imaging-based brain function mapping: a deep learning perspective. [PDF]

Psychoradiology
Zhao L.
europepmc   +1 more source

DeepFeat: A Bottom Up and Top Down Saliency Model Based on Deep Features of Convolutional Neural Nets

, 2017
Ali Mahdi, Jun Qin
openalex   +2 more sources

Machine Learning for Organic Fluorescent Materials

Aggregate, EarlyView.
Organic fluorescent materials (OFMs) have demonstrated significant potential in diverse applications. Conventional approaches for studying OFMs face significant limitations in fluorescence spectroscopy and computational methods. Machine learning (ML) has revolutionized materials chemistry, offering superior predictive accuracy and efficiency over ...
Jiamin Zhong, Wei Zhu, Shoutao Shen, Nan Zhou, Meiyang Xi, Kui Du, Dong Wang, Ben Zhong Tang   +7 more
wiley   +1 more source

Three-dimensional automated segmentation of adolescent idiopathic scoliosis on computed tomography driven by deep learning: A retrospective study. [PDF]

Medicine (Baltimore)
Ji Y, Mei X, Tan R, Zhang W, Ma Y, Peng Y, Zhang Y.   +6 more
europepmc   +1 more source

Artificial Quantum Neural Network: quantum neurons, logical elements and tests of convolutional nets

, 2018
V. I. Dorozhinsky, Oleg Pavlovsky
openalex   +2 more sources

Predicting both thermodynamic and kinetic properties of crystallizing molecules via transformer‐based language model

AIChE Journal, EarlyView.
Abstract Crystallization is pivotal in the chemical and pharmaceutical industry, affecting particle stability, and drug release. Crystal size distribution (CSD), a critical attribute of the final dosage form, is determined by the molecular structure of the crystallizing entity.
Silabrata Pahari, Chi Ho Lee, Niranjan Sitapure, Joseph Sang‐Il Kwon   +3 more
wiley   +1 more source

Deep learning in image segmentation for cancer. [PDF]

J Med Radiat Sci
Rai R.
europepmc   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

Advanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren, Qian Jiang, Xin Jin, Puming Wang, Xing Chu, Shaowen Yao, Shengfa Miao   +6 more
wiley   +1 more source

Accuracy of artificial intelligence-based segmentation in maxillofacial structures: a systematic review. [PDF]

BMC Oral Health
Alahmari M, Alahmari M, Almuaddi A, Abdelmagyd H, Rao K, Hamdoon Z, Alsaegh M, Chaitanya NCSK, Shetty S.   +8 more
europepmc   +1 more source

Waste Classification using Deep Learning Convolution Neural Nets

, 2020
Divy Mohan Rai and Ms. ShikhaGupta
openalex   +1 more source