Searched for: subject%3A%22DNN%22
(1 - 12 of 12)
document
Buijnsters, Jan (author)
Industry 4.0 and the Industrial Internet of Things (IIoT) growth will result in an explosion of data generated by connected devices. Adapting 5G and 6G technology could be the leading enabler of the broad possibilities of connecting IIoT devices in masses. However, the edge solution has some disadvantages, such as the loss of resource elasticity...
master thesis 2023
document
Nembhani, Prithvish Vijaykumar (author)
Artificial intelligence, machine learning, and deep learning have been the buzzwords in almost every industry (medical, automotive, defense, security, finance, etc.) for the last decade. As the market moves towards AI-based solutions, so does the computation need for these solutions increase and change with time. With the rise of smart cities...
master thesis 2023
document
Pérez-Dattari, Rodrigo (author), Kober, J. (author)
Learning from humans allows nonexperts to program robots with ease, lowering the resources required to build complex robotic solutions. Nevertheless, such data-driven approaches often lack the ability to provide guarantees regarding their learned behaviors, which is critical for avoiding failures and/or accidents. In this work, we focus on...
journal article 2023
document
Sharma, Bhawana (author), Sharma, Lokesh (author), Lal, C. (author)
IoT has gained immense popularity recently with advancements in technologies and big data. IoT network is dynamically increasing with the addition of devices, and the big data is generated within the network, making the network vulnerable to attacks. Thus, network security is essential, and an intrusion detection system is needed. In this...
conference paper 2023
document
van der Horst, Casper (author)
For my Master’s thesis, I developed and trained an audio-based localization system for indoor localization called AudioLocNet. AudioLocNet is based on convolutional neural networks and maps recordings from a small(10cm diameter) microphone array to a grid of locations around said array. AudioLocNet was made to be used by swarms of small robots...
master thesis 2022
document
Kevin Shidqi, Kevin (author)
With recent breakthroughs in AI (Artificial Intelligence) technology, the impact of AI on society can be felt in various fields. The market for AI software, for example, reached a valuation of \$62 billion in 2022. A growing number of new computer architectures specialized in running these AI software were also developed. At first they were run...
master thesis 2022
document
Cox, B.A. (author), Birke, Robert (author), Chen, Lydia Y. (author)
Deep neural networks (DNNs) are becoming the core components of many applications running on edge devices, especially for real time image-based analysis. Increasingly, multi-faced knowledge is extracted by executing multiple DNNs inference models, e.g., identifying objects, faces, and genders from images. It is of paramount importance to...
journal article 2022
document
Sharma, Bhawana (author), Sharma, Lokesh (author), Lal, C. (author)
IoT is widely used in many fields, and with the expansion of the network and increment of devices, there is the dynamic growth of data in IoT systems, making the system more vulnerable to various attacks. Nowadays, network security is the primary issue in IoT, and there is a need for the system to detect intruders. In this paper, we constructed...
conference paper 2022
document
Zhang, Qinglong (author), Han, Rui (author), Xin, Gaofeng (author), Liu, Chi Harold (author), Wang, Guoren (author), Chen, Lydia Y. (author)
Deep neural networks (DNNs) have been showing significant success in various anomaly detection applications such as smart surveillance and industrial quality control. It is increasingly important to detect anomalies directly on edge devices, because of high responsiveness requirements and tight latency constraints. The accuracy of DNN-based...
journal article 2022
document
Chilakala, Koteswararao (author)
Diabetic Retinopathy (DR) is one of the leading causes of permanent vision loss. Its current prevalence is around 45 millions across the globe and is projected to 70 million by 2045. Most of the people with this disease condition belong to remote and low income settings. We can reduce this incidence, if quality medical care is accessible in...
master thesis 2021
document
Cox, Bart (author)
Deep neural networks (DNNs) are becoming the core components of many applications running on edge devices,especially for image-based analysis, e.g., identifying objects, faces, and genders. While very successful in resource rich environments like the cloud of powerful computers, utilizing Deep Learning on edge devices for inference is not used...
master thesis 2020
document
Koning, Tim (author)
Reinforcement Learning (RL) is a learning paradigm where an agent learns a task by trial and error. The agent needs to explore its environment and by simultaneously receiving rewards it learns what is appropriate behaviour.<br/>Even though it has roots in machine learning, RL is essentially different from other machine learning methods. In...
master thesis 2020
Searched for: subject%3A%22DNN%22
(1 - 12 of 12)