Inputoutput Hardware Strategies For Cellular Neural Networks

• doi: 10.1109/ICNN.1994.374449
• title: Input/output hardware strategies for cellular neural networks
• publisher: IEEE
• isbn: 0-7803-1901-X
• issn:
• partnum: 94CH3429-8
• rank: 2787
• access_type: LOCKED
• content_type: Conferences
• abstract: In this paper hardware alternatives for the input/output circuits of a cellular neural network are discussed. Cellular neural networks are primarily applied in image processing applications. The realisation of a fully programmable 128/spl times/128 cellular neural network is possible in a standard state of the art CMOS process. Moreover, several alternatives for the integration of a solid-state image sensor that are compatible with a standard CMOS process have been published. The different possible input/output structures are evaluated towards their compatibility with both techniques. They provide the link towards the realisation of a smart image sensor and processor based on cellular neural networks.<>
• article_number: 374449
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=374449
• html_url: https://ieeexplore.ieee.org/document/374449/
• abstract_url: https://ieeexplore.ieee.org/document/374449/
• publication_title: Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)
• conference_location: Orlando, FL, USA
• conference_dates: 28 June-2 July 1994
• publication_number: 3013
• is_number: 8558
• publication_year: 1994
• publication_date: 28 June-2 July 1994
• start_page: 1899
• end_page: 1902 vol.3
• citing_paper_count: 1
• citing_patent_count: 0
• download_count: 62
• insert_date: 20020806
• index_terms:
  • ieee_terms:
    • Neural network hardware
    • Cellular neural networks
    • Image sensors
    • Image processing
    • CMOS process
    • Very large scale integration
    • Integrated circuit interconnections
    • CMOS image sensors
    • CMOS technology
    • Solid state circuits
  • dynamic_index_terms:
    • Cellular Networks
    • Network Of Cells
    • Cellular Neural Networks
    • Image Processing
    • Image Sensor
    • Camera Sensor
    • Smart Sensors
    • Image Processing Applications
    • Standard CMOS
    • Continuous-time
    • Continuous Signal
    • Sources Of Error
    • Edge Detection
    • Output Image
    • Sensor Cells
    • Different Types Of Sensors
    • Shift Register
    • Output Series
    • Serial Output
    • Systematic Sources
    • Extra Hardware
    • Separate Sensors
• isbn_formats:
  • format: Print ISBN, value: 0-7803-1901-X, isbnType: Historical
• authors:
  • Author Name: P. Kinget
    Affiliation: ES AT-MICAS, Katholieke Universiteit Leuven, Heverlee, Belgium
    Author URL: https://ieeexplore.ieee.org/author/37268120200
    ID: 37268120200
    Order: 1
    Author Affiliations:
    • ES AT-MICAS, Katholieke Universiteit Leuven, Heverlee, Belgium
  • Author Name: M. Steyaert
    Affiliation: ES AT-MICAS, Katholieke Universiteit Leuven, Heverlee, Belgium
    Author URL: https://ieeexplore.ieee.org/author/37274261800
    ID: 37274261800
    Order: 2
    Author Affiliations:
    • ES AT-MICAS, Katholieke Universiteit Leuven, Heverlee, Belgium

Image Sensor

• sensor_type: CMOS
• resolution: 128x128 or 512x512
• dynamic_range: Not explicitly mentioned
• pixel_size: Not explicitly mentioned
• dark_current: Not explicitly mentioned

Optical Data

• focal_length: Not explicitly mentioned
• aperture: Not explicitly mentioned
• field_of_view: Not explicitly mentioned
• distortion: Not explicitly mentioned

Performance Metrics

• frame_rate: 25 fps
• signal_to_noise_ratio: Not explicitly mentioned
• sensitivity: Not explicitly mentioned
• shutter_speed: Not explicitly mentioned
• power_consumption: Not explicitly mentioned
• noise: Not explicitly mentioned

Applications & Benefits

• cell_imaging: Image processing applications such as edge detection, range finding, filling, and connected component detection.
• benefits: High speed, high integration density, low power consumption, adaptable to various application needs.

Supporting Organizations

• supported_by: Belgian National Fund for Scientific Research.

Manuscript Details

• publication_date: 28 June-2 July 1994

Relevancy Score

• score: 8
• missing_fields:
  • fill factor
  • quantum efficiency
  • readout speed
  • temporal noise
  • fixed-pattern noise
  • analog-to-digital conversion techniques
  • microlenses
  • on-chip color filters
  • global or rolling shutters
  • backside illumination

Processed JSON Filename

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