2022
DOI: 10.3390/electronics11101604
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A Review on Deep Learning Techniques for IoT Data

Abstract: Continuous growth in software, hardware and internet technology has enabled the growth of internet-based sensor tools that provide physical world observations and data measurement. The Internet of Things(IoT) is made up of billions of smart things that communicate, extending the boundaries of physical and virtual entities of the world further. These intelligent things produce or collect massive data daily with a broad range of applications and fields. Analytics on these huge data is a critical tool for discove… Show more

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Cited by 94 publications
(58 citation statements)
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“…For the diagnosis of brain tumors, many deep learning models have been used, although object detection methods have only been used in a limited number of studies, e.g., Pereira and co-authors employed the 3D Unet model, a new deep learning model that aids in the classification of tumors according to their severity. It has considered two areas of interest, the first of which is the whole brain, and the second of which is the malignancies zone of interest [1,15].…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…For the diagnosis of brain tumors, many deep learning models have been used, although object detection methods have only been used in a limited number of studies, e.g., Pereira and co-authors employed the 3D Unet model, a new deep learning model that aids in the classification of tumors according to their severity. It has considered two areas of interest, the first of which is the whole brain, and the second of which is the malignancies zone of interest [1,15].…”
Section: Related Workmentioning
confidence: 99%
“…We use the test picture to obtain information about the tumor once the model has been trained. Using pretrained parameters on a dataset is a common approach in deep learning models [15]. The new network can now be trained using the transferred parameters as initialization (a process known as fine-tuning as shown in Figure 2), or additional layers can be built on top of the network, with only the new layers being trained on the dataset of interest.…”
Section: Proposed Modelmentioning
confidence: 99%
“…The study helped in redesigning of the curriculum and related resources in flipped class room. The study in [26][27][28] suggested the use of AI in English education system that helped to analyze the various factors pertaining to learning adaptability. The results of the study enabled academicians to propose strategies that improved students' English education.…”
Section: Modelmentioning
confidence: 99%
“…The dynamic properties of the model were compared, and their impact on memory and nonlinear processing capability was analyzed. The study in [36][37][38] proposed a programmable ultraefficient memristor-based accelerator (PUMA) had helped to enhance the memristor crossbars having general purpose execution units. The objective was to accelerate the various forms of machine learning inference workloads.…”
Section: Related Workmentioning
confidence: 99%