Matches in SemOpenAlex for { <https://semopenalex.org/work/W3121049197> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W3121049197 endingPage "103923" @default.
- W3121049197 startingPage "103923" @default.
- W3121049197 abstract "Abstract The moving image processing can now be applied to the economic analysis of the imaging target's movement by the high-speed shooting. This method is, consider some of the common approaches. For this reason, the acknowledgement of the movement recognition and movement following are talked about. These projects, not successive autonomous moreover. As of late, Field-Programmable Gate Array (FPGA) is wide, particularly in the versatile and installed gadgets have been utilized in equipment quickening agent for the execution of Convolutional Neural Network (CNN). A CNN dependent on FPGA has been proposed. It is intended to assemble a neural organization convolution with the streamlining and advancement of the memory of the profoundly reusable quickening agent work is low equipment asset utilization. Movement, position, speed, and key data of the camera's objective can catch any ideal data from the caught casing can be shipped off the framework's investigation parts. To follow the moving objects by recognizing movement location is one of these smart frameworks. Even though there is another technique for identifying a moving there, these strategies, there are a few impediments for constant applications. Hence, to give precise outcomes with this strategy, the foundation deduction technique is reasonable for constant applications." @default.
- W3121049197 created "2021-01-18" @default.
- W3121049197 creator A5007400451 @default.
- W3121049197 creator A5048869202 @default.
- W3121049197 creator A5077379337 @default.
- W3121049197 date "2021-04-01" @default.
- W3121049197 modified "2023-10-18" @default.
- W3121049197 title "Motion image processing system based on multi core FPGA processor and convolutional neural Network" @default.
- W3121049197 cites W1991965723 @default.
- W3121049197 cites W2064980387 @default.
- W3121049197 cites W2071689678 @default.
- W3121049197 cites W2096367565 @default.
- W3121049197 cites W2121689659 @default.
- W3121049197 cites W2133995198 @default.
- W3121049197 cites W2142571850 @default.
- W3121049197 cites W2158790918 @default.
- W3121049197 cites W2783834599 @default.
- W3121049197 cites W3101868689 @default.
- W3121049197 cites W3102673529 @default.
- W3121049197 cites W2100949463 @default.
- W3121049197 doi "https://doi.org/10.1016/j.micpro.2021.103923" @default.
- W3121049197 hasPublicationYear "2021" @default.
- W3121049197 type Work @default.
- W3121049197 sameAs 3121049197 @default.
- W3121049197 citedByCount "4" @default.
- W3121049197 countsByYear W31210491972021 @default.
- W3121049197 countsByYear W31210491972022 @default.
- W3121049197 countsByYear W31210491972023 @default.
- W3121049197 crossrefType "journal-article" @default.
- W3121049197 hasAuthorship W3121049197A5007400451 @default.
- W3121049197 hasAuthorship W3121049197A5048869202 @default.
- W3121049197 hasAuthorship W3121049197A5077379337 @default.
- W3121049197 hasConcept C118524514 @default.
- W3121049197 hasConcept C149635348 @default.
- W3121049197 hasConcept C154945302 @default.
- W3121049197 hasConcept C173608175 @default.
- W3121049197 hasConcept C2164484 @default.
- W3121049197 hasConcept C31972630 @default.
- W3121049197 hasConcept C41008148 @default.
- W3121049197 hasConcept C42935608 @default.
- W3121049197 hasConcept C50644808 @default.
- W3121049197 hasConcept C76155785 @default.
- W3121049197 hasConcept C78766204 @default.
- W3121049197 hasConcept C81363708 @default.
- W3121049197 hasConcept C9390403 @default.
- W3121049197 hasConceptScore W3121049197C118524514 @default.
- W3121049197 hasConceptScore W3121049197C149635348 @default.
- W3121049197 hasConceptScore W3121049197C154945302 @default.
- W3121049197 hasConceptScore W3121049197C173608175 @default.
- W3121049197 hasConceptScore W3121049197C2164484 @default.
- W3121049197 hasConceptScore W3121049197C31972630 @default.
- W3121049197 hasConceptScore W3121049197C41008148 @default.
- W3121049197 hasConceptScore W3121049197C42935608 @default.
- W3121049197 hasConceptScore W3121049197C50644808 @default.
- W3121049197 hasConceptScore W3121049197C76155785 @default.
- W3121049197 hasConceptScore W3121049197C78766204 @default.
- W3121049197 hasConceptScore W3121049197C81363708 @default.
- W3121049197 hasConceptScore W3121049197C9390403 @default.
- W3121049197 hasLocation W31210491971 @default.
- W3121049197 hasOpenAccess W3121049197 @default.
- W3121049197 hasPrimaryLocation W31210491971 @default.
- W3121049197 hasRelatedWork W1566136542 @default.
- W3121049197 hasRelatedWork W1823313045 @default.
- W3121049197 hasRelatedWork W2002703587 @default.
- W3121049197 hasRelatedWork W2163077378 @default.
- W3121049197 hasRelatedWork W2369375926 @default.
- W3121049197 hasRelatedWork W2373880775 @default.
- W3121049197 hasRelatedWork W2811290777 @default.
- W3121049197 hasRelatedWork W3217667592 @default.
- W3121049197 hasRelatedWork W39695077 @default.
- W3121049197 hasRelatedWork W4255428424 @default.
- W3121049197 hasVolume "82" @default.
- W3121049197 isParatext "false" @default.
- W3121049197 isRetracted "false" @default.
- W3121049197 magId "3121049197" @default.
- W3121049197 workType "article" @default.