Results 11 to 20 of about 9,883,756 (332)
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 +3 more
doaj +4 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 +2 more
semanticscholar +9 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 +1 more
doaj +4 more sources
DL-AMDet: Deep learning-based malware detector for android
Intelligent Systems with ApplicationsThe 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 +2 more
doaj +4 more sources
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 +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 +4 more sources
DL-Reg: A Deep Learning Regularization Technique using Linear Regression [PDF]
CoRR, 2020 Regularization plays a vital role in the context of deep learning by preventing deep neural networks from the danger of overfitting. This paper proposes a novel deep learning regularization method named as DL-Reg, which carefully reduces the nonlinearity of deep networks to a certain extent by explicitly enforcing the network to behave as much linear ...
Maryam Dialameh +2 more
core +6 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 +3 more
doaj +5 more sources
WARC-DL: Scalable Web Archive Processing for Deep Learning
CoRR, 2022 Submitted to OSSYM 2022 - 4th International Open Search ...
Deckers, Niklas, Potthast, Martin
openaire +4 more sources
Facial Expression Recognition Using Deep Learning (DL)
International Journal of Scientific Research in Engineering and ManagementAbstract - Facial Expression Recognition (FER) plays an important role in intelligent human–computer interaction systems by enabling machines to understand human emotions automatically. This paper presents a deep learning-based facial expression recognition system designed for real-time emotion detection with improved stability and accuracy.
Arpita S. Parsankar +3 more
openaire +2 more sources