Search results for "deep learning"
showing 10 items of 337 documents
LightSleepNet: A Lightweight Deep Model for Rapid Sleep Stage Classification with Spectrograms.
2021
Deep learning has achieved unprecedented success in sleep stage classification tasks, which starts to pave the way for potential real-world applications. However, due to its enormous size, deployment of deep neural networks is hindered by high cost at various aspects, such as computation power, storage, network bandwidth, power consumption, and hardware complexity. For further practical applications (e.g., wearable sleep monitoring devices), there is a need for simple and compact models. In this paper, we propose a lightweight model, namely LightSleepNet, for rapid sleep stage classification based on spectrograms. Our model is assembled by a much fewer number of model parameters compared to…
One and Two Dimensional Convolutional Neural Networks for Seizure Detection Using EEG Signals
2021
Deep learning for the automated detection of epileptic seizures has received much attention during recent years. In this work, one dimensional convolutional neural network (1D-CNN) and two dimensional convolutional neural network (2D-CNN) are simultaneously used on electroencephalogram (EEG) data for seizure detection. Firstly, using sliding windows without overlap on raw EEG to obtain the definite one-dimension time EEG segments (1D-T), and continuous wavelet transform (CWT) for 1D-T signals to obtain the two-dimension time-frequency representations (2D-TF). Then, 1D-CNN and 2D-CNN model architectures are used on 1D-T and 2D-TF signals for automatic classification, respectively. Finally, t…
Algorytmy — nowy wymiar nadzoru i kontroli nad świadczącym pracę
2020
Autor wskazuje, że algorytmy stają się kluczową technologią władzy nad świadczącym pracę. Pozwalają na sformatowanie zarówno samych pracowników, jak i wzajemnych oddziaływań między nimi zasadniczo w jednym celu — optymalizacji procesów pracy służących zwiększeniu wydajności. Z tej perspektywy pracownik jest cyfrowym modelem zbudowanym z danych i informacji. Oznacza to, że wszelkie jego ekspresje ujawniane w środowisku pracy będą mogły być mierzalne, i to na rożne sposoby. Algorytmy rzucają również nowe światło na zagadnienie podporządkowania w zatrudnieniu. A wszystko dzięki ,,wtapianiu się” ich w środowisko danych biometrycznych osób świadczących pracę. W pewien sposób przejmują one własno…
On Attacking Future 5G Networks with Adversarial Examples : Survey
2022
The introduction of 5G technology along with the exponential growth in connected devices is expected to cause a challenge for the efficient and reliable network resource allocation. Network providers are now required to dynamically create and deploy multiple services which function under various requirements in different vertical sectors while operating on top of the same physical infrastructure. The recent progress in artificial intelligence and machine learning is theorized to be a potential answer to the arising resource allocation challenges. It is therefore expected that future generation mobile networks will heavily depend on its artificial intelligence components which may result in …
IMAGE ORIENTATION WITH A HYBRID PIPELINE ROBUST TO ROTATIONS AND WIDE-BASELINES
2022
Abstract. The extraction of reliable and repeatable interest points among images is a fundamental step for automatic image orientation (Structure-From-Motion). Despite recent progresses, open issues in challenging conditions - such as wide baselines and strong light variations - are still present. Over the years, traditional hand-crafted methods have been paired by learning-based approaches, progressively updating the state-of-the-art according to recent benchmarks. Notwithstanding these advancements, learning-based methods are often not suitable for real photogrammetric surveys due to their lack of rotation invariance, a fundamental requirement for these specific applications. This paper p…
Reti sismiche urbane per monitoraggio sismico monitoraggio strutturale ed allerta precoce
2021
In questa tesi, viene effettuato un analisi preliminare in cui si mette in evidenza come l'italia sia un paese a rischio sismico, poichè possiede molti centri storici con strutture non progettate per eventi sismici di media entità. Si è prestato molta attenzione su quante vite umane vengono salvate dopo un terremoto catastrofico. L'analisi fa emergere come, è importante essere tempestivi nell'estrarre le persone rimaste sotto le macerie, poichè la percentuale di persone estratte vive si mantiene alta solo entro le 48 ore dall'evento. Dopo 96 ore questa percentule si attesta a 0. In eventi passati spesso i soccorsi sono arrivati con giorni di ritardo nelle zone più devastate. L'obbiettivo ch…
STCMS: A Smart Thermal Comfort Monitor For Senior People
2020
Undoubtedly, the steady increase in the number of elderly people is not to be underestimated. These demographic changes call attention to new challenges regarding adequate aging-in-place strategies. Since the majority of the senior population spend up to 90% of their time indoors, appropriate and comfortable housing represents an important foundation for such strategies. In this respect, different types of data gathered from sensors, connected devices, and Internet of Things (IoT) technologies come to play an important role to support services for the elderly population in indoor environments. One of the aspects of concern is thermal comfort. In this paper, we introduce a new deep learning-…
Generalization Capacity Analysis of Non- Intrusive Load Monitoring using Deep Learning
2020
Appliance Load Monitoring is a technique used to monitor devices existing in homes, industry or naval vessels. Acquisition of device-level data can provide great benefits in many areas such as energy management, demand response, and load forecasting. However, the monitoring process is often provided with a costly installation, as it requires a large number of sensors and a data center. Non-Intrusive Load Monitoring (NILM) is an alternative and cost-efficient load monitoring solution. Simply put, NILM is the process of obtaining device-level data by analyzing the aggregated data read from the main meter that measures the electricity consumption of the whole house. Before NILM analysis is per…
MODELLING, OPTIMIZATION, AND 3E-ANALYSIS OF DISH-STIRLING CONCENTRATING SOLAR POWER SYSTEMS
2022
raggiungimento degli obiettivi del precedente Accordo di Parigi, tutti i Paesi sono stati invitati a impegnarsi a garantire l'azzeramento globale entro la metà del secolo e a mantenere l'aumento della temperatura media globale significativamente al di sotto dei 2 °C, rispetto ai livelli preindustriali, entro il 2050, e più precisamente entro il limite superiore di 1,5 °C. Tutti i Paesi stanno concentrando le loro politiche su una transizione energetica globale che consiste nell'aumento dell'uso di fonti rinnovabili per la generazione di elettricità e nell'uso diretto di calore e biomassa rinnovabili, nell'uso diretto di elettricità pulita nei trasporti e nelle applicazioni termiche, nel mig…
Classification of EEG signals for prediction of epileptic seizures
2022
Epilepsy is a common brain disorder that causes patients to face multiple seizures in a single day. Around 65 million people are affected by epilepsy worldwide. Patients with focal epilepsy can be treated with surgery, whereas generalized epileptic seizures can be managed with medications. It has been noted that in more than 30% of cases, these medications fail to control epileptic seizures, resulting in accidents and limiting the patient’s life. Predicting epileptic seizures in such patients prior to the commencement of an oncoming seizure is critical so that the seizure can be treated with preventive medicines before it occurs. Electroencephalogram (EEG) signals of patients recorded to ob…