Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Machine learning approaches to IoT security: A systematic literature review
With the continuous expansion and evolution of IoT applications, attacks on those IoT
applications continue to grow rapidly. In this systematic literature review (SLR) paper, our …
applications continue to grow rapidly. In this systematic literature review (SLR) paper, our …
[PDF][PDF] The computational limits of deep learning
Deep learning's recent history has been one of achievement: from triumphing over humans
in the game of Go to world-leading performance in image classification, voice recognition …
in the game of Go to world-leading performance in image classification, voice recognition …
Intelligent video surveillance: a review through deep learning techniques for crowd analysis
Big data applications are consuming most of the space in industry and research area.
Among the widespread examples of big data, the role of video streams from CCTV cameras …
Among the widespread examples of big data, the role of video streams from CCTV cameras …
Deep learning models for cloud, edge, fog, and IoT computing paradigms: Survey, recent advances, and future directions
In recent times, the machine learning (ML) community has recognized the deep learning
(DL) computing model as the Gold Standard. DL has gradually become the most widely …
(DL) computing model as the Gold Standard. DL has gradually become the most widely …
[HTML][HTML] Reliability of analog resistive switching memory for neuromorphic computing
As artificial intelligence calls for novel energy-efficient hardware, neuromorphic computing
systems based on analog resistive switching memory (RSM) devices have drawn great …
systems based on analog resistive switching memory (RSM) devices have drawn great …
A study on different deep learning algorithms used in deep neural nets: MLP SOM and DBN
J Naskath, G Sivakamasundari, AAS Begum - Wireless personal …, 2023 - Springer
Deep learning is a wildly popular topic in machine learning and is structured as a series of
nonlinear layers that learns various levels of data representations. Deep learning employs …
nonlinear layers that learns various levels of data representations. Deep learning employs …
[HTML][HTML] Futuristic view of the internet of quantum drones: review, challenges and research agenda
The disruptive technology of unmanned aerial vehicles (UAVs), or drones, is a trend with
increasing applications and practical relevance in the current and future society. Despite the …
increasing applications and practical relevance in the current and future society. Despite the …
Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers
With quantum computing technologies nearing the era of commercialization and quantum
supremacy, machine learning (ML) appears as one of the promising'killer'applications …
supremacy, machine learning (ML) appears as one of the promising'killer'applications …
Artificial intelligence and internet of things (AI-IoT) technologies in response to COVID-19 pandemic: A systematic review
The origin of the COVID-19 pandemic has given overture to redirection, as well as
innovation to many digital technologies. Even after the progression of vaccination efforts …
innovation to many digital technologies. Even after the progression of vaccination efforts …