Results 11 to 20 of about 267,347 (270)

DL-LA: Deep Learning Leakage Assessment

Transactions on Cryptographic Hardware and Embedded Systems, 2021
In recent years, deep learning has become an attractive ingredient to side-channel analysis (SCA) due to its potential to improve the success probability or enhance the performance of certain frequently executed tasks.
Thorben Moos, Felix Wegener, Amir Moradi
doaj   +4 more sources

Deep Learning (DL)-Enabled System for Emotional Big Data [PDF]

IEEE Access, 2021
Emotion care for human well-being is important for all ages. In this paper, we propose an emotion care system based on big data analysis for autism disorder patient training, where emotion is detected in terms of facial expression.
Haopeng Wang, Diana P. Tobon V., M. Shamim Hossain, Abdulmotaleb El Saddik   +3 more
doaj   +2 more sources

Electroencephalographic (EEG) based Deep Learning (DL): A Comparative Review

Al-Iraqia Journal for Scientific Engineering Research, 2023
Deep learning (DL) has recently shown great promise in supporting knowledge of electroencephalographic (EEG) as a result of its ability to discover visual features (feature representation) from original (raw) data.
Riyadh Salam Mohammed, Ammar A. Al-Hamadani   +1 more
doaj   +3 more sources

DL-RMD: a geophysically constrained electromagnetic resistivity model database (RMD) for deep learning (DL) applications [PDF]

Earth System Science Data, 2023
Deep learning (DL) algorithms have shown incredible potential in many applications. The success of these data-hungry methods is largely associated with the availability of large-scale datasets, as millions of observations are often required to achieve ...
M. R. Asif, M. R. Asif, M. R. Asif, N. Foged, N. Foged, T. Bording, T. Bording, J. J. Larsen, J. J. Larsen, A. V. Christiansen, A. V. Christiansen   +10 more
doaj   +3 more sources

DL-TODA: A Deep Learning Tool for Omics Data Analysis

Biomolecules, 2023
Metagenomics is a technique for genome-wide profiling of microbiomes; this technique generates billions of DNA sequences called reads. Given the multiplication of metagenomic projects, computational tools are necessary to enable the efficient and ...
Cecile M. Cres, Andrew Tritt, Kristofer E. Bouchard, Ying Zhang   +3 more
doaj   +5 more sources

DL-AMDet: Deep learning-based malware detector for android

Intelligent Systems with Applications
The Android operating system, with its market share leadership and open-source nature in smartphones, has become the primary target of malware. However, detecting malicious Android processes has become a significant challenge because of the complexity of
Ahmed R. Nasser, Ahmed M. Hasan, Amjad J. Humaidi   +2 more
doaj   +2 more sources

Deep-Learning-Based Segmentation of Cells and Analysis (DL-SCAN)

Biomolecules
With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to studying cellular properties and signaling in living cells and tissues.
Alok Bhattarai, Jan Meyer, Laura Petersilie, Syed I. Shah, Louis A. Neu, Christine R. Rose, Ghanim Ullah   +6 more
doaj   +3 more sources

How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset [PDF]

Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021
Deep Learning Hard (DL-HARD) is a new annotated dataset designed to more effectively evaluate neural ranking models on complex topics. It builds on TREC Deep Learning (DL) topics by extensively annotating them with question intent categories, answer types, wikified entities, topic categories, and result type metadata from a commercial web search engine.
Mackie, Iain, Dalton, Jeff, Yates, Andrew   +2 more
openaire   +5 more sources

Impact of Deep learning-DL in the modern computational biology

European Journal of Volunteering and Community-Based Projects, 2021
Deep learning (DL) has shown unstable improvement in its application to bioinformatics and has displayed thrillingly promising capacity to mine the complex relationship disguised in immense degree natural and biomedical data.
Muhammad Mazhar Fareed
doaj   +3 more sources

Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review

IEEE Access, 2021
Deep learning (DL)-based PV Power Forecasting (PVPF) emerged nowadays as a promising research direction to intelligentize energy systems. With the massive smart meter integration, DL takes advantage of the large-scale and multi-source data ...
Mohamed Massaoudi, Ines Chihi, Haitham Abu-Rub, Shady S. Refaat, Fakhreddine S. Oueslati   +4 more
doaj   +1 more source