Results 11 to 20 of about 2,716,934 (278)

Generalization in Deep Learning

, 2022
Published by Cambridge University Press.
Kawaguchi, Kenji, Bengio, Yoshua, Kaelbling, Leslie Pak   +2 more
openaire   +3 more sources

Deep attentive video summarization with distribution consistency learning [PDF]

, 2021
This article studies supervised video summarization by formulating it into a sequence-to-sequence learning framework, in which the input and output are sequences of original video frames and their predicted importance scores, respectively.
Han, Jungong, Ji, Zhong, Li, Xi, Pang, Yanwei, Zhao, Yuxiao   +4 more
core   +1 more source

Effective prediction finite element model of pull-out capacity for cast-in-place anchor in high strain rate effects

Scientific Reports, 2023
Cast-in-place anchors are being increasingly used in many applications including building construction, bridge, and power plants. The anchorage to concrete systems are subjected to tensile, shear and combined loads from a variety of loading circumstances
Quoc To Bao, Kihak Lee, Hyoseo An, Do Hyung Lee, Jiuk Shin   +4 more
doaj   +1 more source

An Improved Blind Kriging Surrogate Model for Design Optimization Problems

Mathematics, 2022
Surrogate modeling techniques are widely employed in solving constrained expensive black-box optimization problems. Therein, Kriging is among the most popular surrogates in which the trend function is considered as a constant mean.
Hau T. Mai, Jaewook Lee, Joowon Kang, H. Nguyen-Xuan, Jaehong Lee   +4 more
doaj   +1 more source

DL2: A Deep Learning-Driven Scheduler for Deep Learning Clusters [PDF]

IEEE Transactions on Parallel and Distributed Systems, 2021
More and more companies have deployed machine learning (ML) clusters, where deep learning (DL) models are trained for providing various AI-driven services. Efficient resource scheduling is essential for maximal utilization of expensive DL clusters.
Yanghua Peng, Yixin Bao, Yangrui Chen, Chuan Wu 0001, Chen Meng, Wei Lin 0016   +5 more
openaire   +2 more sources

Predicting positron emission tomography brain amyloid positivity using interpretable machine learning models with wearable sensor data and lifestyle factors

Alzheimer’s Research & Therapy, 2023
Background Developing a screening method for identifying individuals at higher risk of elevated brain amyloid burden is important to reduce costs and burden to patients in clinical trials on Alzheimer’s disease or the clinical setting.
Noriyuki Kimura, Tomoki Aota, Yasuhiro Aso, Kenichi Yabuuchi, Kotaro Sasaki, Teruaki Masuda, Atsuko Eguchi, Yoshitaka Maeda, Ken Aoshima, Etsuro Matsubara   +9 more
doaj   +1 more source

Deep learning in bioinformatics [PDF]

Briefings in Bioinformatics, 2016
In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields.
Seonwoo Min, Byunghan Lee, Sungroh Yoon
openaire   +3 more sources

Unconstrained neighbor selection for minimum reconstruction error-based K-NN classifiers

Complex & Intelligent Systems, 2023
It is essential to define more convincing and applicable classifiers for small datasets. In this paper, a minimum reconstruction error-based K-nearest neighbors (K-NN) classifier is proposed. We propose a new neighbor selection method.
Rassoul Hajizadeh
doaj   +1 more source

Discovery of E2730, a novel selective uncompetitive GAT1 inhibitor, as a candidate for anti‐seizure medication

Epilepsia Open, 2023
Objective As of 2022, 36 anti‐seizure medications (ASMs) have been licensed for the treatment of epilepsy, however, adverse effects (AEs) are commonly reported.
Kazuyuki Fukushima, Hiroyuki Higashiyama, Yuji Kazuta, Keisuke Hashimoto, Naoto Watanabe, Yoshiaki Furuya, Yoshimasa Ito, Ting Wu, Takashi Kosasa, Delia M. Talos, Yeri Song, Nicholas S. Roberts, Frances E. Jensen, Takahisa Hanada, Katsutoshi Ido   +14 more
doaj   +1 more source

Deep learning-based anomalous object detection system powered by microcontroller for PTZ cameras [PDF]

, 2018
Automatic video surveillance systems are usually designed to detect anomalous objects being present in a scene or behaving dangerously. In order to perform adequately, they must incorporate models able to achieve accurate pattern recognition in an image,
Benito Picazo, Jesús, Domínguez-Merino, Enrique, López-Rubio, Ezequiel, Ortiz-de-lazcano-Lobato, Juan Miguel, Palomo, Esteban J.   +4 more
core   +1 more source