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020 _a9783031601408
_9978-3-031-60140-8
024 7 _a10.1007/978-3-031-60140-8
_2doi
050 4 _aTK5101-5105.9
072 7 _aTJK
_2bicssc
072 7 _aTEC041000
_2bisacsh
072 7 _aTJK
_2thema
100 1 _aGhani, Arfan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981970
245 1 0 _aInnovations in Computer Vision and Data Classification
_h[electronic resource] :
_bFrom Pandemic Data Analysis to Environmental and Health Monitoring /
_cby Arfan Ghani.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXIV, 148 p. 100 illus., 75 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aEAI/Springer Innovations in Communication and Computing,
_x2522-8609
505 0 _aIntroduction -- Accelerating the classification of pandemic data using reconfigurable hardware (FPGA) and machine learning -- Computer vision based automated diagnosis for skin cancer detection -- Design and development of an integrated analytics platform for environmental data classification -- Design and development of multimodal healthcare data sensing and classification using Deep Neural Networks (DNNs) -- Low-power analogue design with Spiking Neural Networks (SNN) -- Full custom design of a sustainable, low-power environmental monitoring node -- Real-time performance analysis of Maximum-Power-Point Tracking (MPPT) algorithm for energy conversion on hardware platform (FPGA) -- Computer-vision based real data generation for object classification -- Conclusion.
520 _aThis book delves into the dynamic realm of data classification, focusing on its real-world applications. Through an insightful journey, readers are introduced to the practical applications of reconfigurable hardware, machine learning, computer vision, and neuromorphic circuit design across diverse domains. The author explores topics such as the role of Field-Programmable Gate Arrays (FPGAs) in expediting pandemic data analysis and the transformative impact of computer vision on healthcare. Additionally, the book delves into environmental data classification, energy-efficient solutions for deep neural network applications, and real-time performance analysis of energy conversion algorithms. With the author's guidance, readers are led through practical implementations, ensuring a comprehensive grasp of each subject matter. Whether a seasoned researcher, engineer, or student, this book equips readers with the tools to make data-driven decisions, optimize systems, and innovate solutions across various fields, from healthcare to environmental monitoring. Explores advancements in data classification, encompassing FPGA acceleration, neuromorphic hardware, and computer vision-based diagnosis; Presents data classification through real-world examples from healthcare, environmental science, and energy conversion, employing applied machine learning and deep neural networks; Includes guidance on the application of complex concepts with ease through a didactic approach and hands-on instruction.
650 0 _aTelecommunication.
650 0 _aArtificial intelligence
_xData processing.
650 0 _aComputational intelligence.
_964052
650 1 4 _aCommunications Engineering, Networks.
650 2 4 _aData Science.
650 2 4 _aComputational Intelligence.
_964052
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031601392
776 0 8 _iPrinted edition:
_z9783031601415
776 0 8 _iPrinted edition:
_z9783031601422
830 0 _aEAI/Springer Innovations in Communication and Computing,
_x2522-8609
_965695
856 4 0 _uhttps://doi.org/10.1007/978-3-031-60140-8
912 _aZDB-2-ENG
912 _aZDB-2-SXE
999 _c62267
_d62267