Relevant bibliographies by topics / Intel Movidius

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Intel Movidius'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Intel Movidius"

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Dinelli, Gianmarco, Gabriele Meoni, Emilio Rapuano, Gionata Benelli, and Luca Fanucci. "An FPGA-Based Hardware Accelerator for CNNs Using On-Chip Memories Only: Design and Benchmarking with Intel Movidius Neural Compute Stick." International Journal of Reconfigurable Computing 2019 (October 22, 2019): 1–13. http://dx.doi.org/10.1155/2019/7218758.

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During the last years, convolutional neural networks have been used for different applications, thanks to their potentiality to carry out tasks by using a reduced number of parameters when compared with other deep learning approaches. However, power consumption and memory footprint constraints, typical of on the edge and portable applications, usually collide with accuracy and latency requirements. For such reasons, commercial hardware accelerators have become popular, thanks to their architecture designed for the inference of general convolutional neural network models. Nevertheless, field-programmable gate arrays represent an interesting perspective since they offer the possibility to implement a hardware architecture tailored to a specific convolutional neural network model, with promising results in terms of latency and power consumption. In this article, we propose a full on-chip field-programmable gate array hardware accelerator for a separable convolutional neural network, which was designed for a keyword spotting application. We started from the model implemented in a previous work for the Intel Movidius Neural Compute Stick. For our goals, we appropriately quantized such a model through a bit-true simulation, and we realized a dedicated architecture exclusively using on-chip memories. A benchmark comparing the results on different field-programmable gate array families by Xilinx and Intel with the implementation on the Neural Compute Stick was realized. The analysis shows that better inference time and energy per inference results can be obtained with comparable accuracy at expenses of a higher design effort and development time through the FPGA solution.
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Agarwal, Surabhi, Elena Hervas-Martin, Jonathan Byrne, Aubrey Dunne, Jose Luis Espinosa-Aranda, and David Rijlaarsdam. "An Evaluation of Low-Cost Vision Processors for Efficient Star Identification." Sensors 20, no. 21 (November 2, 2020): 6250. http://dx.doi.org/10.3390/s20216250.

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Star trackers are navigation sensors that are used for attitude determination of a satellite relative to certain stars. A star tracker is required to be accurate and also consume as little power as possible in order to be used in small satellites. While traditional approaches use lookup tables for identifying stars, the latest advances in star tracking use neural networks for automatic star identification. This manuscript evaluates two low-cost processors capable of running a star identification neural network, the Intel Movidius Myriad 2 Vision Processing Unit (VPU) and the STM32 Microcontroller. The intention of this manuscript is to compare the accuracy and power usage to evaluate the suitability of each device for use in a star tracker. The Myriad 2 VPU and the STM32 Microcontroller have been specifically chosen because of their performance on computer vision algorithms alongside being cost-effective and low power consuming devices. The experimental results showed that the Myriad 2 proved to be efficient and consumed around 1 Watt of power while maintaining 99.08% accuracy with an input including false stars. Comparatively the STM32 was able to deliver comparable accuracy (99.07%) and power measurement results. The proposed experimental setup is beneficial for small spacecraft missions that require low-cost and low power consuming star trackers.
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Leon, Vasileios, George Lentaris, Evangelos Petrongonas, Dimitrios Soudris, Gianluca Furano, Antonis Tavoularis, and David Moloney. "Improving Performance-Power-Programmability in Space Avionics with Edge Devices: VBN on Myriad2 SoC." ACM Transactions on Embedded Computing Systems 20, no. 3 (April 2021): 1–23. http://dx.doi.org/10.1145/3440885.

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The advent of powerful edge devices and AI algorithms has already revolutionized many terrestrial applications; however, for both technical and historical reasons, the space industry is still striving to adopt these key enabling technologies in new mission concepts. In this context, the current work evaluates an heterogeneous multi-core system-on-chip processor for use on-board future spacecraft to support novel, computationally demanding digital signal processors and AI functionalities. Given the importance of low power consumption in satellites, we consider the Intel Movidius Myriad2 system-on-chip and focus on SW development and performance aspects. We design a methodology and framework to accommodate efficient partitioning, mapping, parallelization, code optimization, and tuning of complex algorithms. Furthermore, we propose an avionics architecture combining this commercial off-the-shelf chip with a field programmable gate array device to facilitate, among others, interfacing with traditional space instruments via SpaceWire transcoding. We prototype our architecture in the lab targeting vision-based navigation tasks. We implement a representative computer vision pipeline to track the 6D pose of ENVISAT using megapixel images during hypothetical spacecraft proximity operations. Overall, we achieve 2.6 to 4.9 FPS with only 0.8 to 1.1 W on Myriad2 , i.e., 10-fold acceleration versus modern rad-hard processors. Based on the results, we assess various benefits of utilizing Myriad2 instead of conventional field programmable gate arrays and CPUs.
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Muchtar, Kahlil, Chairuman, Yudha Nurdin, and Afdhal Afdhal. "Pendeteksian Septoria pada Tanaman Tomat dengan Metode Deep Learning berbasis Raspberry Pi." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 5, no. 1 (February 20, 2021): 107–13. http://dx.doi.org/10.29207/resti.v5i1.2831.

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much needed to meet the needs of both industry and households. However, tomato plants still require serious handling in increasing the yields. Data from the Central Bureau of Statistics shows that the number of tomatoes produced is not in accordance with a large number of market demands, resulting from the decrease of tomato yields. One of the obstacles in increasing tomato production is that the crops are attacked by septoria leaf spot disease due to the fungus or the fungus Septoria Lycopersici Speg. Most farmers have limited knowledge of the early symptoms, which are not obvious, and also facing difficulty in detecting this disease earlier. The problem has been causing disadvantages such as crop failure or plant death. Based on this problem, a study will be conducted with the aim of designing a tool that can be used to detect septoria leaf spot disease based on deep learning using the Convolutional Neural Network (ConvNets or CNN) model, where an algorithm that resembles human nerves is one of the supervised learning and widely used for solving linear and non-linear problems. In addition, the researcher used the Raspberry Pi as a microcontroller and used the Intel Movidius Neural Computing Stick (NCS) which functions to speed up the computing process so that the detection process is easier because of its portable, fast and accurate nature. The average accuracy rate is 95.89% with detection accuracy between 84.22% to 100%.
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Rathour, Navjot, Sultan S. Alshamrani, Rajesh Singh, Anita Gehlot, Mamoon Rashid, Shaik Vaseem Akram, and Ahmed Saeed AlGhamdi. "IoMT Based Facial Emotion Recognition System Using Deep Convolution Neural Networks." Electronics 10, no. 11 (May 28, 2021): 1289. http://dx.doi.org/10.3390/electronics10111289.

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Facial emotion recognition (FER) is the procedure of identifying human emotions from facial expressions. It is often difficult to identify the stress and anxiety levels of an individual through the visuals captured from computer vision. However, the technology enhancements on the Internet of Medical Things (IoMT) have yielded impressive results from gathering various forms of emotional and physical health-related data. The novel deep learning (DL) algorithms are allowing to perform application in a resource-constrained edge environment, encouraging data from IoMT devices to be processed locally at the edge. This article presents an IoMT based facial emotion detection and recognition system that has been implemented in real-time by utilizing a small, powerful, and resource-constrained device known as Raspberry-Pi with the assistance of deep convolution neural networks. For this purpose, we have conducted one empirical study on the facial emotions of human beings along with the emotional state of human beings using physiological sensors. It then proposes a model for the detection of emotions in real-time on a resource-constrained device, i.e., Raspberry-Pi, along with a co-processor, i.e., Intel Movidius NCS2. The facial emotion detection test accuracy ranged from 56% to 73% using various models, and the accuracy has become 73% performed very well with the FER 2013 dataset in comparison to the state of art results mentioned as 64% maximum. A t-test is performed for extracting the significant difference in systolic, diastolic blood pressure, and the heart rate of an individual watching three different subjects (angry, happy, and neutral).
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Santos, Elismar Alves dos. "A dimensão psíquica do fundamentalismo religioso." Revista Eclesiástica Brasileira 77, no. 308 (December 31, 2017): 837–51. http://dx.doi.org/10.29386/reb.v77i308.15.

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Síntese: Neste artigo, o autor reflete sobre a dimensão psíquica do fundamentalismo religioso, mostrando como se dá o processo de repressão da vivência espiritual. Para indivíduos fundamentalistas e neuróticos, encontrar um substituto para a repressão do espiritual significa optar pelo fundamentalismo religioso. O fundamentalismo religioso manifesta-se a partir de atitudes concretas de pessoas e grupos. Pessoas que pertencem a grupos fundamentalistas têm um nome e uma história. Por isso, é importante acentuar algumas particularidades da estrutura de personalidade de indivíduos que agem movidos por seus ideais fundamentalistas. Indivíduos com tendência ao radicalismo fundamentalista podem entrar numa desordem caótica devido à repressão. O fundamentalismo religioso seria a manifestação do que foi reprimido ao longo do processo de construção da personalidade?Palavras-chave: Neurose. Personalidade. Psicopatologia. Fundamentalismo religioso. Diálogo inter-religioso.Abstract: In this article, the author talks about the psychological dimension of religious fundamentalism, showing how the process of repression of spiritual experience occurs. For fundamentalist and neurotic individuals, finding a substitute for spiritual repression means opting for religious fundamentalism. Religious fundamentalism manifests itself from the concrete attitudes of people and groups. People who belong to fundamentalist groups have a name and a history. It is therefore important to emphasize some particularities of the personality structure of individuals who act driven by their fundamentalist ideals. Individuals prone to fundamentalist radicalism may enter into chaotic disorder due to repression. Could religious fundamentalism be the manifestation of what was repressed throughout the personality construction process?Keywords: Neurosis. Personality. Psychopathology. Religious fundamentalism. Interreligious dialogue.
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"Adaboost Cascade Classifier for Classification and Identification of Wild Animals using Movidius Neural Compute Stick." International Journal of Engineering and Advanced Technology 9, no. 1S3 (December 31, 2019): 495–99. http://dx.doi.org/10.35940/ijeat.a1089.1291s319.

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Deep learning has gone deeper and has been utilized in almost all the applications like object recognition, image classification, speech recognition and much more. Most of the real-time applications rely on deep learning for accurate results. But one downside to the deep learning is its demand for GPUs (Graphical Processing Unit) or TPUs (Tensor Processing Units) for faster execution. There was no one-stop-shop hardware and software for deep learning applications, until recently Intel launched the Movidius Neural Compute Stick (NCS). This sleek device provides the power of GPU in a CPU based system. In this work, we have modeled an animal detection system using NCS and AdaBoost classifier powered by Multi-Block Local Binary Pattern (MB-LBP) features. The model has been built upon AlexNet and has achieved an average accuracy of 96.8% and a false rate 2.3% in classifying the animals as wild and non-wild. Furthermore, the model has a speedup of 467% when compared to the execution in the CPU based system.
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"Surveillance Camera using Face Recognition for Automatic Attendance Feeder and Energy Conservation in Classroom." International Journal of Recent Technology and Engineering 8, no. 4 (November 30, 2019): 3222–25. http://dx.doi.org/10.35940/ijrte.d8033.118419.

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This works gives solution to two most important problems in the universities by equipping a surveillance camera with Artificial Intelligence (AI) technology. The first problem solved is unnecessary time wastage in manual and bio-metric (fingerprint based) attendance marking for students. The second problem solved is the unnecessary electricity wastage in classrooms without occupants. Using the videos getting recorded in surveillance cameras, the number of heads detection and face recognition is done. When there is no occupants in the class, the number of heads detected will be zero. So we can cut-off the electricity supply for that classroom. With the face recognition process the attendance for the students will be get automatically marked. The Intel movidius stick does the work of face recognition and finding the head counts.
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Evangelista, Rafael De Almeida, and Felipe Fonseca. "Reconhecimento e superação da exploração capitalista em redes criativas de colaboração e produção | Recognizing and overcoming capitalist exploitation in creative networks of collaboration and production." Liinc em Revista 12, no. 1 (May 31, 2016). http://dx.doi.org/10.18617/liinc.v12i1.861.

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RESUMO O industrialismo, como chaga desumanizadora, vem sendo encarado como algo a ser vencido pelo menos desde o início do século XX (senão antes). O caminho para isso, para a superação da frieza mecânica das máquinas de ferro, explosão, fumaça e força, movidas por trabalho alienante, tem sido apontado como uma busca do entendimento do funcionamento e de “retorno” ao orgânico, a sistemas produtivos tidos como mais flexíveis, naturais, feitos de carne, sangue, calor e leveza. A modelagem feita sobre os sistemas biológicos e da vida subsidiou o desenvolvimento das tecnologias de informação e comunicação, e, respectivamente, esses sistemas têm sido usados como exemplares para explicar uma certa “natureza” das redes informáticas como auto-organizadas, evolucionárias e emergentes. Este texto busca inter-relacionar a analogia sobre sistemas de computação biológica – como desenvolvida por Tiziana Terranova –, tomada como o modo típico de gerenciamento dessas redes, com pesquisas de campo de caráter etnográfico que informam sobre laboratórios digitais e outros ambientes de produção colaborativa e reflexões de natureza política sobre relações de exploração econômica dadas nesses ambientes. O imaginário tecnoutópico, que funciona como pano de fundo para esses laboratórios e outros ambientes de criação, afirma as tecnologias de informação como instrumentos de combate à burocratização e à alienação da sociedade. Contudo, este trabalho procura ir além dessas imagens – questionando suas origens e pressupostos naturalizantes –, ao mesmo tempo que afirma as possibilidades de resistência e reinvenção diante do capitalismo informacional de matriz cibernética, contidas nos espaços de criação. Explora-se aqui a possibilidade de uma relação ambígua, por isso mesmo interessante, entre as tentativas de controle e extração produtiva, de gerenciamento capitalista de ambientes criativos, horizontalizados e emergentes, e a constituição de alternativas e de modos de vida paralelos e independentes da sociedade de consumo de mercadorias.As redes informacionais são, na atualidade, exploradas como máquinas de produção com comportamento emergente, não centralizado, e, por isso, criativas. Podem ser concomitantemente espaços de constituição de uma vida fora (e para além) do capitalismo?Palavras-chave: Cultura e Poder; Cibercultura; Economia Política; Internet; Trabalho.ABSTRACT Industrialism as a dehumanizing scourge has been seen since the early twentieth century (if not before) as something to be overcome. The road to overcome the mechanical coldness of the machines of iron, explosion, smoke and strength, fueled by alienating work, has been touted as a "return" to the organic, to production systems that are seen as more flexible, more natural, made of meat, blood, warmth and lightness. The functioning model of biological life systems has subsidized the development of information and communication technologies and these systems have been used as examples to explain a certain "nature" of computer networks as self-organizing, evolutionary and emerging systems. This article aims to discuss the analogy of biological computing systems as developed by Tiziana Terranova, taken as the typical way of managing creative networks. We use ethnographic field research on digital laboratories and other collaborative production environments and add to that political reflections on economic relations of exploitation that happen in these environments. The technoutopian imaginary, which acts as a backdrop to these laboratories and other creative environments, says information technology can be used as tools to combat bureaucratization and alienation in society. However, this paper seeks to go beyond these images – questioning their origins and naturalized assumptions – while claiming that resistance and reinvention are possible against the informational capitalism cyber matrix. We explore the possibility of an ambiguous relationship between attempts by capitalist management to control and extract value from horizontal and emerging spaces and the establishment of parallel and independent ways of life within capitalist society.Nowadays, information networks are being used as production machines with emergent and decentralized behavior, therefore creative. Can they be concurrently set up as spaces for life outside (and beyond) capitalism?Keywords: Culture and Power; Cyberculture; Political Economy; Internet; Labour.
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Dissertations / Theses on the topic "Intel Movidius"

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Lukáč, Jakub. "Sledování osob v záznamu z dronu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417275.

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Práca rieši možnosť zaznamenávať pozíciu osôb v zázname z kamery drona a určovať ich polohu. Absolútna pozícia sledovanej osoby je odvodená vzhľadom k pozícii kamery, teda vzhľadom k umiestneniu drona vybaveného príslušnými senzormi. Zistené dáta sú po ich spracovaní vykreslené ako príslušné cesty. Práca si ďalej dáva za cieľ využiť dostupné riešenia čiastkových problémov: detekcia osôb v obraze, identifikácie jednotlivých osôb v čase, určenie vzdialenosti objektu od kamery, spracovanie potrebných senzorových dát. Následne využiť preskúmané metódy a navrhnúť riešenie, ktoré bude v reálnom čase pracovať na uvedenom probléme. Implementačná časť spočíva vo využití akcelerátoru Intel NCS v spojení s Raspberry Pi priamo ako súčasť drona. Výsledný systém je schopný generovať výstup o polohe osôb v zábere kamery a príslušne ho prezentovať.
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Míček, Vojtěch. "Neuronové sítě pro klasifikaci typu a kvality průmyslových výrobků." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2020. http://www.nusl.cz/ntk/nusl-413276.

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The aim of this master's thesis thesis is to enable evaluation of quality, or the type of product in industrial applications using artificial neural networks, especially in applications where the classical approach of machine vision is too complicated. The system thus designed is implemented onto a specific hardware platform and becomes a subject to the final optimalisation for the hardware platform for the best performance of the system.
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Lukáč, Jakub. "Sledování osob ve videu z dronu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445483.

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Práca rieši možnosť zaznamenávať pozíciu osôb v zázname z kamery drona a určovať ich polohu. Absolútna pozícia sledovanej osoby je odvodená vzhľadom k pozícii kamery, teda vzhľadom k umiestneniu drona vybaveného príslušnými senzormi. Zistené dáta sú po ich spracovaní vykreslené ako príslušné cesty v grafe. Práca si ďalej dáva za cieľ využiť dostupné riešenia čiastkových problémov: detekcia osôb v obraze, identifikácia jednotlivých osôb v čase, určenie vzdialenosti objektu od kamery, spracovanie potrebných senzorových dát. Následne využiť preskúmané metódy a navrhnúť riešenie, ktoré bude v reálnom čase pracovať na uvedenom probléme. Implementačná časť spočíva vo využití akcelerátoru Intel NCS v spojení s Raspberry Pi priamo ako súčasť drona. Výsledný systém je schopný generovať výstup o polohe detekovaných osôb v zábere kamery a príslušne ho prezentovať.
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Book chapters on the topic "Intel Movidius"

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Rathour, Navjot, Pranab Kumar Mishra, Kartik Gaur, and Abhishek Maddheshiya. "Raspberry-Pi and Intel Movidius Assisted Framework for Fruit Quality Monitoring." In Intelligent Circuits and Systems, 368–73. London: CRC Press, 2021. http://dx.doi.org/10.1201/9781003129103-57.

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Rathour, Navjot, Rajesh Singh, and Anita Gehlot. "Fast method of face recognition in real time using Raspberry-Pi and Intel Movidius NCS." In Intelligent Circuits and Systems, 318–24. London: CRC Press, 2021. http://dx.doi.org/10.1201/9781003129103-50.

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Conference papers on the topic "Intel Movidius"

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Marantos, Charalampos, Nikolaos Karavalakis, Vasileios Leon, Vasileios Tsoutsouras, Kiamal Pekmestzi, and Dimitrios Soudris. "Efficient support vector machines implementation on Intel/Movidius Myriad 2." In 2018 7th International Conference on Modern Circuits and Systems Technologies (MOCAST). IEEE, 2018. http://dx.doi.org/10.1109/mocast.2018.8376630.

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Bakshi, Suyash, and Lennart Johnsson. "A Highly Efficient SGEMM Implementation using DMA on the Intel/Movidius Myriad-2." In 2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD). IEEE, 2020. http://dx.doi.org/10.1109/sbac-pad49847.2020.00051.

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Kyriakos, Angelos, Elissaios-Alexios Papatheofanous, Bezaitis Charalampos, Evangelos Petrongonas, Dimitrios Soudris, and Dionysios Reisis. "Design and Performance Comparison of CNN Accelerators Based on the Intel Movidius Myriad2 SoC and FPGA Embedded Prototype." In 2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO). IEEE, 2019. http://dx.doi.org/10.1109/iccairo47923.2019.00030.

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