Results 31 to 40 of about 134,020 (300)

Scaling tabular data of training datasets with neural networks

Вісник Харківського національного університету імені В.Н. Каразіна. Серія: Математичне моделювання, інформаційні технології, автоматизовані системи управління, 2023
The paper proposes a method of scaling the tabular data of the training dataset using neural networks, describes the architecture of such networks. Relevance.
Дмитро Узлов, Анастасія Морозова, Вікторія Кузнєцова, Кирило Руккас   +3 more
doaj   +1 more source

Robustness and Explainability of Deep Neural Networks: Architectures and Applications [PDF]

, 2020
In this work, I study the performance, robustness, and explainability of machine learning models, in particular deep neural networks, and propose their respective solutions.
Chirag Agarwal (9907857)
core   +1 more source

Artificial intelligence used in genome analysis studies

The EuroBiotech Journal, 2018
Next Generation Sequencing (NGS) or deep sequencing technology enables parallel reading of multiple individual DNA fragments, thereby enabling the identification of millions of base pairs in several hours.
D’Agaro Edo
doaj   +1 more source

Deep learning in bladder cancer imaging: A review

Frontiers in Oncology, 2022
Deep learning (DL) is a rapidly developing field in machine learning (ML). The concept of deep learning originates from research on artificial neural networks and is an upgrade of traditional neural networks.
Mingyang Li, Zekun Jiang, Wei Shen, Haitao Liu   +3 more
doaj   +1 more source

Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users [PDF]

, 2022
Modern deep learning methods constitute incredibly powerful tools to tackle a myriad of challenging problems. However, since deep learning methods operate as black boxes, the uncertainty associated with their predictions is often challenging to quantify.
Jospin, L.V., Bennamoun, M., Buntine, Wray, Laga, Hamid, Boussaid, F., Bennamoun, Mohammed, Boussaid, Farid, Laga, H., Jospin, Laurent Valentin, Buntine, W., Farid Boussaid, Laurent Valentin Jospin, Hamid Laga, Wray Buntine, Mohammed Bennamoun   +14 more
core   +1 more source

Artificial intelligence in surgical pathology

Journal of Pathology of Nepal, 2019
Artificial intelligence (AI) is machine intelligence that mimics human cognitive function. It denotes the intelligence presented by some artificial entities including computers and robots.
Gopi Aryal
doaj   +1 more source

Which Artificial Intelligence Algorithm Better Predicts the Chinese Stock Market?

IEEE Access, 2018
Unpredictable stock market factors make it difficult to predict stock index futures. Although efforts to develop an effective prediction method have a long history, recent developments in artificial intelligence and the use of artificial neural networks ...
Lin Chen, Zhilin Qiao, Minggang Wang, Chao Wang, Ruijin Du, Harry Eugene Stanley   +5 more
doaj   +1 more source

Deep learning in Emergency Medicine: Recent contributions and methodological challenges

Emergency Care Journal, 2020
In the last few years, artificial intelligence (AI) technology has grown dramatically impacting several fields of human knowledge and medicine in particular.
Francesco Faita
doaj   +1 more source

Review of dynamic gesture recognition

Virtual Reality & Intelligent Hardware, 2021
In recent years, gesture recognition has been widely used in the fields of intelligent driving, virtual reality, and human-computer interaction. With the development of artificial intelligence, deep learning has achieved remarkable success in computer ...
Yuanyuan SHI, Yunan LI, Xiaolong FU, M.I.A.O. Kaibin, M.I.A.O. Qiguang   +4 more
doaj   +1 more source

Foundations and Advances in Deep Learning [PDF]

, 2014
Deep neural networks have become increasingly popular under the name of deep learning recently due to their success in challenging machine learning tasks.
Cho, Kyunghyun
core   +1 more source