Results 291 to 300 of about 9,883,756 (332)

Deep Learning (DL) Based On-board Indirect Useful Life Prediction

2020 IEEE International Conference on Consumer Electronics (ICCE), 2020
On-board diagnostics (OBD) of mechanical parts, such as suspension and chassis, is a long-standing challenge for commercial vehicle because: 1. Direct sensing is not possible on production truck; 2. Customer usage and external environment greatly affect remaining useful life.
Wenbo Yu, Yong Sun, Aishwarya Kadam, Yuting Chen   +3 more
openaire   +2 more sources

DL-dashboard

Companion Proceedings of the 24th International Conference on Intelligent User Interfaces, 2019
In recent years, deep learning has contributed to a big step forward in artificial intelligence, so that deep learning models have been created extensively in a variety of areas. However, development of deep learning model requires high implementation skills as well as domain knowledge.
Yoo-Mi Park, Eun-Ji Lim, Shin-Young Ahn, Wan Choi 0002, Taewoo Kim 0003   +4 more
openaire   +1 more source

Machine and Deep Learning (ML/DL) Algorithms, Frameworks, and Libraries

2023
Each primary, secondary, tertiary, quaternary, and the quinary sector has huge or very huge incremental data from large-scale, small-scale industries, medium industries, or cottage industries. The data associated with each of them are very crucial from every point of view.
Jigna Bhupendra Prajapati, Savan Patel, Richesh Gaurav, Dhvanil Nileshkumar Prajapati, Kavita Saini   +4 more
openaire   +1 more source

Automatic Analysis of Happy/Sad Face Image with Deep Learning Model

2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN)
Deep learning (DL) is often used for detecting and analysing images. Because they are more accurate, the DL methods are often used in different ways to look at images to identify the best way to solve the problem at hand. This study uses a DL-model-based
A. R., Mohammad Musa Al-Momani, Md. Tabil Ahammed, Sorabh Lakhanpal, J. Bino, S. Prabha   +5 more
semanticscholar   +1 more source

TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling

International Conference on Learning Representations
Deep learning architectures for supervised learning on tabular data range from simple multilayer perceptrons (MLP) to sophisticated Transformers and retrieval-augmented methods.
Yu. V. Gorishniy, Akim Kotelnikov, Artem Babenko   +2 more
semanticscholar   +1 more source

Deep Learning-based Intrusion Detection Systems: A Survey

arXiv.org
Intrusion Detection Systems (IDS) have long been a hot topic in the cybersecurity community. In recent years, with the introduction of deep learning (DL) techniques, IDS have made great progress due to their increasing generalizability.
Zhi-Wei Xu, Yu-Juan Wu, Shi-Heng Wang, Jia-Bao Gao, Tian Qiu, Ziqi Wang, Hai Wan, Xi-Bin Zhao   +7 more
semanticscholar   +1 more source

DL-GSA: A Deep Learning Metaheuristic Approach to Missing Data Imputation

2018
Incomplete data has emerged as a prominent problem in the fields of machine learning, big data and various other academic studies. Due to the surge in deep learning techniques for problem-solving, in this paper, authors have proposed a deep learning-metaheuristic approach to combat the problem of imputing missing data.
Ayush Garg 0003, Deepika Naryani, Garvit Aggarwal, Swati Aggarwal   +3 more
openaire   +1 more source

Large Language Models are Edge-Case Generators: Crafting Unusual Programs for Fuzzing Deep Learning Libraries

International Conference on Software Engineering
Bugs in Deep Learning (DL) libraries may affect almost all downstream DL applications, and it is crucial to ensure the quality of such systems. It is challenging to generate valid input programs for fuzzing DL libraries, since the input programs need to ...
Yin-Lin Deng, Chun Xia, Chenyuan Yang, S. Zhang, Shu-Jing Yang, Ling-Ming Zhang   +5 more
semanticscholar   +1 more source

DL-ASD: A Deep Learning Approach for Autism Spectrum Disorder

2022 5th International Conference on Contemporary Computing and Informatics (IC3I), 2022
Ruchi Mittal, Varun Malik, Ajay Rana
openaire   +2 more sources

Cough-DL: A Deep Learning Model for Ear-Worn Cough Detection

2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Cough serves as a crucial bio-marker for evaluation and monitoring of pulmonary conditions. With growing interest towards automatic cough detection systems, it's important to acknowledge the existing hurdles on the way for a robust cough counter. These include high false positive rate caused by cough-like sounds in the environment, reduced sensitivity ...
Bhawana Chhaglani, Ebrahim Nemati, Sharath Chandrashekhara, Jilong Kuang, Alex Gao 0001   +4 more
openaire   +3 more sources