Results 71 to 80 of about 134,020 (300)

Using unsupervised machine learning for fault identification in virtual machines [PDF]

, 2015
Self-healing systems promise operating cost reductions in large-scale computing environments through the automated detection of, and recovery from, faults. However, at present there appears to be little known empirical evidence comparing the different
Schneider, Christopher
core   +1 more source

Data Analysis for Linguistic, Cultural, and Historical Research III : Deep Learning

, 2022
This course is a theoretical and methodological introduction to modern cutting-edge methods in advanced data analysis with a primary focus on deep learning and artificial intelligence.
Jeffrey Richard Tharsen
core   +1 more source

Implantable Ionic Memristors Based on Natural Polymer Heterojunctions

Advanced Functional Materials, EarlyView.
We report an implantable natural polymer‐based ionic memristor composed of hyaluronic acid, chitosan, and PDMS. The device achieved 98.94% accuracy in MNIST classification while reducing training time by 36.8% compared with a conventional artificial neural network (ANN).
Dong‐yup Lee, Byung Ik Park, Gihyeon Yim, Hyunjae Yoo, Sangjun Ma, Jundong Park, Jeong‐Yun Sun   +6 more
wiley   +1 more source

Providing a Foresight Model for Selecting the Appropriate Breast Cancer Diagnosis Model [PDF]

مجله انفورماتیک سلامت و زیست پزشکی
Introduction: Selecting an appropriate model for breast cancer diagnosis is critical. Unsuitable models can compromise diagnostic accuracy, lead to incorrect outcomes, and impact clinical decision-making.
Abdolhossein Shakibaeinia, Mohsen Chagin, Amin Golabpour, Ahmad Khosravi   +3 more
doaj  

Leveraging chaotic transients in the training of artificial neural networks

Physical Review Research
Traditional algorithms to optimize artificial neural networks when confronted with a supervised learning task are usually exploitation-type relaxational dynamics such as gradient descent (GD).
Pedro Jiménez-González, Miguel C. Soriano, Lucas Lacasa   +2 more
doaj   +1 more source

Norse - A deep learning library for spiking neural networks

, 2021
Norse is a library that aims to exploit the advantages of bio-inspired neural components, which are sparse and event-driven - a fundamental difference from artificial neural networks.
Pehle, Christian-Gernot, Pedersen, Jens Egholm   +1 more
core   +1 more source

Multimode Oxide‐Based Optoelectronic Memtransistor for In‐Sensor Vision Processing

Advanced Functional Materials, EarlyView.
A multimode optoelectronic memtransistor (OEMT) is demonstrated for vision explainable artificial intelligence (VXAI) hardware. By integrating optical sensing, electrical masking, and non‐volatile memory, the device enables key operations required for generating saliency information.
Min Gu Lee, Geunyoung Kim, Hwa Young Kim, Do Hoon Kim, Hanchan Song, Huisu Noh, Jungwan Noh, Seungwoo Lee, Sang‐Hee Ko Park, Himchan Cho, Kyung Min Kim   +10 more
wiley   +1 more source

Artificial intelligence in industrial heat exchanger fouling prediction: A 20-year systematic review of AI, ML, and DL approaches

ICT Express
Fouling in heat exchangers (HXs) affects various industries by lowering efficiency and increasing costs. Traditional fouling-prediction models often do not reflect important mechanistic information and thus become very complex and less reliable.
Abdul Wahid Soomro, Miss Laiha Mat Kiah, Rafidah Md Noor, Salim Newaz Kazi, Kaleemullah Shaikh, Wajahat Ahmed Khan, Ihsan Ali   +6 more
doaj   +1 more source

Toward Scalable, Efficient, and Accurate Deep Spiking Neural Networks With Backward Residual Connections, Stochastic Softmax, and Hybridization

Frontiers in Neuroscience, 2020
Spiking Neural Networks (SNNs) may offer an energy-efficient alternative for implementing deep learning applications. In recent years, there have been several proposals focused on supervised (conversion, spike-based gradient descent) and unsupervised ...
Priyadarshini Panda, Sai Aparna Aketi, Kaushik Roy   +2 more
doaj   +1 more source

Urban sound classification using artificial neural networks. [PDF]

, 2019
In this thesis the main goal was to compare artificial neural network classification capabilities in the context of urban sound classification. In this work, theoretical analysis related to artificial intelligence, machine learning, neural networks is ...
Gilys, Tomas,
core