Results 61 to 70 of about 7,201 (183)
Navigational Path Detection Using Fuzzy Binarization and Hough Transform
Journal of the Korea Society of Computer and Information, 2014 In conventional methods for car navigational path detection using Hough transform, navigational path deviation of a car is decided in car navigational images with simple background. But in case of car navigational images having complex background with obstacles on the road, shadows, other cars, and so on, it is very difficult to detect navigational ...
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Advanced Intelligent Systems, Volume 7, Issue 10, October 2025.A thorough analysis of event‐based vision for flapping‐wing robots is presented, with emphasis on hardware integration, suitability under challenging flight conditions, and real‐time performance. Theoretical and experimental studies demonstrate how these sensors enable robust and efficient onboard perception for ornithopters, thereby advancing autonomy
Raul Tapia +5 more
wiley +1 more source
Design of automatic vision-based inspection system for solder joint segmentation [PDF]
, 2009 Purpose: Computer vision has been widely used in the inspection of electronic components. This paper proposes a computer vision system for the automatic detection, localisation, and segmentation of solder joints on Printed Circuit Boards (PCBs) under ...
Fookes, Clinton +2 more
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Incremental Art: A Neural Network System for Recognition by Incremental Feature Extraction [PDF]
, 1994 Incremental ART extends adaptive resonance theory (ART) by incorporating mechanisms for efficient recognition through incremental feature extraction.
Aguilar, Mario J., Ross, William D.
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WIREs Computational Molecular Science, Volume 15, Issue 5, September/October 2025.This study presents an innovative automated KNIME workflow that integrates document parsing tools and large language models (LLMs) to streamline the extraction of key data from publications. Demonstrating high accuracy, the method enhances data processing efficiency and access, thereby supporting advancements in toxicological research and beyond ...
José Teófilo Moreira‐Filho +12 more
wiley +1 more source
Optic cup segmentation: type-II fuzzy thresholding approach and blood vessel extraction
Clinical Ophthalmology, 2017 Ahmed Almazroa,1 Sami Alodhayb,2 Kaamran Raahemifar,3 Vasudevan Lakshminarayanan1 1School of Optometry and Vision Science, University of Waterloo, Canada; 2Binrushd Ophthalmic Center, Riyadh, Saudi Arabia; 3Department of Electrical Engineering, Ryerson ...
Almazroa A +3 more
doaj
Row Crop's Identication Through Hough Transform using Images Segmented by Robust Fuzzy Possibilistic C-Means [PDF]
, 2011 The Hough transform (HT) is a widely used method for line detection and recognition, due to its robustness. But its performance is strongly dependent on the applied segmentation technique.
Barreiro Elorza, Pilar +2 more
core
Deep Learning‐Based Automated Segmentation of Layered Crater Ejecta on Mars
Journal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 3, September 2025.Abstract Layered crater ejecta (LCE) with fluidization on Mars is generally believed to be related to the near‐surface ice‐bearing deposits. The improvement in the resolution of planetary image data has led to the discovery of more and more LCE, providing support for further research on the formation and geological significance of layered ejecta ...
Xiaoqi He +5 more
wiley +1 more source
Expert Systems, Volume 42, Issue 9, September 2025.ABSTRACT Finding the correct match to a probe image from a vast amount of data is critical for the online retrieval of apparel images. These images are captured under an uncontrolled environment (e.g., viewpoint and illumination changes); therefore, such type of data is extremely challenging in Content‐Based Image Retrieval (CBIR) research.
Marryam Murtaza +5 more
wiley +1 more source
Use the Fuzzy Hough transform towards reduction of the precision/uncertainty duality [PDF]
Pattern Recognition, 1999 The Hough transform is a popular method for detecting complex forms in digital images. However, the technique is not very robust since several parameters that determine the scope of the detection results, such as quantization thresholds and intervals, must first be defined.
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