A Cmos Currentmode Vlsi Implementation Of Cellular Neural Network For An Image Objects Area Estimation

• doi: 10.1109/CNNA.1994.381652
• title: A CMOS current-mode VLSI implementation of cellular neural network for an image objects area estimation
• publisher: IEEE
• isbn: 0-7803-2070-0
• issn:
• partnum: 94TH0693-2
• rank: 587
• access_type: LOCKED
• content_type: Conferences
• abstract: Summary form only given. The paper is concerned with the physical implementation of a CNN which realizes a specific predefined image processing operation. The circuit is intended to be realized in a 1.2 /spl mu/m CMOS process. The VLSI chip is expected to be used as a smart sensor of visual information and its main function is to detect objects with an area which exceeds some user-defined threshold value. For proper operation the circuit should provide an appropriate image preprocessing to cancel the effects of non-uniform image illumination and to suppress image noise. The kernel of the proposed circuit is a reprogrammable CNN, based on the concept of a pulse-mode CNN. The paper presents an architecture of a basic element of the circuit-a reprogrammable cell, designed using the current-mode approach. The proposed cell architecture differs from the solutions presented so far since it is optimized to ensure these processing properties, which are important for proper circuit operation.<>
• article_number: 381652
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=381652
• html_url: https://ieeexplore.ieee.org/document/381652/
• abstract_url: https://ieeexplore.ieee.org/document/381652/
• publication_title: Proceedings of the Third IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-94)
• conference_location: Rome, Italy
• conference_dates: 18-21 Dec. 1994
• publication_number: 3049
• is_number: 8645
• publication_year: 1994
• publication_date: 18-21 Dec. 1994
• start_page: 351
• end_page:
• citing_paper_count: 1
• citing_patent_count: 0
• download_count: 73
• insert_date: 20020806
• index_terms:
  • ieee_terms:
    • Very large scale integration
    • Cellular neural networks
    • Image processing
    • CMOS process
    • Intelligent sensors
    • Object detection
    • Lighting
    • Circuit noise
    • Noise cancellation
    • Kernel
  • dynamic_index_terms:
    • Cellular Neural Networks
    • Time Sequence
    • Image Noise
• isbn_formats:
  • format: Print ISBN, value: 0-7803-2070-0, isbnType: Historical
• authors:
  • Author Name: J. Kowalski
    Affiliation: Institute of Electronics, Technical University of Lódź, Lodz, Poland
    Author URL: https://ieeexplore.ieee.org/author/37447395900
    ID: 37447395900
    Order: 1
    Author Affiliations:
    • Institute of Electronics, Technical University of Lódź, Lodz, Poland
  • Author Name: K. Slot
    Affiliation: Institute of Electronics, Technical University of Lódź, Lodz, Poland
    Author URL: https://ieeexplore.ieee.org/author/37389496900
    ID: 37389496900
    Order: 2
    Author Affiliations:
    • Institute of Electronics, Technical University of Lódź, Lodz, Poland
  • Author Name: T. Kacprzak
    Affiliation: Institute of Electronics, Technical University of Lódź, Lodz, Poland
    Author URL: https://ieeexplore.ieee.org/author/37266345400
    ID: 37266345400
    Order: 3
    Author Affiliations:
    • Institute of Electronics, Technical University of Lódź, Lodz, Poland

Image Sensor

• sensor_type: CMOS
• resolution: unspecified
• dynamic_range: unspecified
• pixel_size: unspecified
• dark_current: unspecified

Optical Data

• focal_length: unspecified
• aperture: unspecified
• field_of_view: unspecified
• distortion: unspecified

Performance Metrics

• frame_rate: unspecified
• signal_to_noise_ratio: unspecified
• sensitivity: unspecified
• shutter_speed: unspecified
• power_consumption: unspecified
• noise: unspecified

Applications & Benefits

• cell_imaging: The CMOS image sensor is intended for visual information processing to detect objects exceeding a defined threshold.
• benefits: Provides smart sensor functionality for image processing.

Supporting Organizations

• supported_by: Technical University of €Mi

Manuscript Details

• publication_date: 18-21 Dec. 1994

Relevancy Score

• score: 8
• missing_fields:
  • resolution
  • dynamic_range
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • frame_rate
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • noise

Processed JSON Filename

request_3cb56937-a13c-486d-9d00-e23e4dd78542-a_cmos_currentmode_vlsi_implementation_of_cellular_neural_network_for_an_image_objects_area_estimation.json