the papers submitted to the Sixthinternationalconference on imageprocessing and itsapplications are presented. the issues considered include shape description and recognition;imageprocessingapplications;texture;...
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the papers submitted to the Sixthinternationalconference on imageprocessing and itsapplications are presented. the issues considered include shape description and recognition;imageprocessingapplications;texture;image segmentation;neural networks;colour;inspection and document processing;filtering and morphology;medical applications;transport, security and remote sensing.
the proceedings contains 93 papers from the 6th IEE internationalconference on imageprocessing and itsapplications. Topics discussed include: image coding and coding standards;interactive multimedia services;medica...
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the proceedings contains 93 papers from the 6th IEE internationalconference on imageprocessing and itsapplications. Topics discussed include: image coding and coding standards;interactive multimedia services;medical radiograph imageprocessing;shape contours progressive polygon encoding;image fractal encoding by classified domain trees;parallel computing;LBG image vector quantization;entropy-constrained design;quadtree video coding schemes;low refresh-rate video sequences compression technique;local motion tracking;semantic-based coding;videophone sequences;and binary-tree recursive motion estimation.
the proceedings contain 86 papers. the topics discussed include: robust real-time monitoring of complex human activities using multi modal video analytics;a robust approach for classifying laparoscopic video distortio...
ISBN:
(纸本)9798331506520
the proceedings contain 86 papers. the topics discussed include: robust real-time monitoring of complex human activities using multi modal video analytics;a robust approach for classifying laparoscopic video distortions using ResNet-50;enhancing x-ray image classification through neural architecture;revolutionary MRI imaging for Alzheimer’s: cutting-edge GANs and vision transformer solutions;advanced deep learning strategies for breast cancer image analysis;identifying surgical instruments in pedagogical cataract surgery videos through an optimized aggregation network;enhancing auxiliary cancer classification task for multi-task breast ultrasound diagnosis network;and bioinspired computer vision for effective extended reality applications.
this paper reviews the latest machine learning and artificial intelligence technology, showcasing its potential to revolutionize the oil and gas industry. Despite the current limitations, the industry is on the brink ...
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the proceedings contains 170 papers. Topics discussed include imageprocessing, image coding, labelling and classification, medical applications, motion, stereo and three dimensional, image analysis, image interpretat...
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the proceedings contains 170 papers. Topics discussed include imageprocessing, image coding, labelling and classification, medical applications, motion, stereo and three dimensional, image analysis, image interpretation, image coding and communications, shape description and recognition, imageprocessingapplications, computer architectures, image segmentation, neural networks, industrial inspection, filtering and morphology, texture and color, transport, security and remote sensing.
To enhance robotic fruit harvesting systems, the proposed methodology uses imageprocessing techniques to recognize orange stems. the method highlights only the stem of an orange fruit in an image by utilizing gray-sc...
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Medical image segmentation plays a pivotal role in computer-aided diagnosis by facilitating the extraction of essential features necessary for disease detection and treatment strategies. the continuous progress in ima...
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Line segment detection is a fundamental procedure in computer vision, pattern recognition, and image analysis applications. the paper proposes a novel method for wide line segment detection especially endpoints determ...
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Computer vision, driven by artificial intelligence, has become pervasive in diverse applications such as self-driving cars and law enforcement. However, the susceptibility of these systems to attacks has raised signif...
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Recent studies point to an accuracy gap between humans and Artificial Neural Network (ANN) models when classifying blurred images, with humans outperforming ANNs. To bridge this gap, we introduce a spectral channel-ba...
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