Abstract
Human deep neural networks (HDNNs) are a type of artificial neural network that is inspired by the structure and function of the human brain. HDNNs are composed of multiple interconnected layers of neurons, which are able to learn complex patterns from data. HDNNs have been shown to be very effective at solving a wide range of problems, including image recognition, natural language processing, and machine translation. HDNNs are often used in conjunction with artificial intelligence (AI) to create intelligent systems that can mimic human cognitive abilities. For example, HDNNs have been used to develop AI systems that can understand and respond to human language, and that can learn from their experiences and improve their performance over time. Human deep neural networks (HDNNs) are a type of artificial neural network that is inspired by the structure and function of the human brain. HDNNs are composed of multiple interconnected layers of neurons, which are able to learn complex patterns from data. HDNNs have been shown to be very effective at solving a wide range of problems, including image recognition, natural language processing, and machine translation. HDNNs are often used in conjunction with artificial intelligence (AI) to create intelligent systems that can mimic human cognitive abilities. For example, HDNNs have been used to develop AI systems that can understand and respond to human language, and that can learn from their experiences and improve their performance over time.
Publisher
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Reference8 articles.
1. A CNN-MLP Deep Model for Sensor-based Human Activity Recognition** by Agti Nadia; Sabri Lyazid; Kazar Okba; Chibani Abdelghani (2023) Research work
2. DeepIQ: A Human-Inspired AI System for Solving IQ Test Problems ** by Jacek Mandizuk; Adam Zychowski (2019) Research work
3. A Survey on Deep Learning for Human Activity Recognition** by Fuqiang Gu; Mu-Huan Chung; Mark Chignell; Shahrokh Valaee (2021) Research work
4. Narayanan, L. G. T., & Padhy, D. S. C. (2023). Artificial Intelligence for Predictive Maintenance of Armoured Fighting Vehicles Engine. In Indian Journal of Artificial Intelligence and Neural Networking (Vol. 3, Issue 5, pp. 1-12). https://doi.org/10.54105/ijainn.e1071.083523
5. Pandey, R., Verma, Dr. H. K., Parakh, Dr. A., & Khare, Dr. C. J. (2022). Artificial Intelligence Based Optimal Placement of PMU. In International Journal of Emerging Science and Engineering (Vol. 10, Issue 11, pp. 1-6). https://doi.org/10.35940/ijese.i2541.10101122
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Human Action Recognition using Long Short-Term Memory and Convolutional Neural Network Model;International Journal of Soft Computing and Engineering;2024-06-30
2. Stock Market Prediction;Indian Journal of Data Mining;2024-05-30
3. Sign Language to Text Conversion using CNN;Indian Journal of Data Mining;2024-05-30
4. LipNet: End-to-End Lipreading;Indian Journal of Data Mining;2024-05-30
5. Driver Distraction and Drowsiness Detection Based on Object Detection Using Deep Learning Algorithm;International Journal of Innovative Technology and Exploring Engineering;2024-05-30