the proceedings contain 90 papers. the topics discussed include: automated vertebra identification from X-ray images;towards non invasive diagnosis of scoliosis using semi-supervised learning approach;articulated mode...
ISBN:
(纸本)3642137741
the proceedings contain 90 papers. the topics discussed include: automated vertebra identification from X-ray images;towards non invasive diagnosis of scoliosis using semi-supervised learning approach;articulated model registration of MRI/X-ray spine data;multimodality image alignment using information-theoretic approach;retinal images: optic disk localization and detection;automatic corneal nerves recognition for earlier diagnosis and follow-up of diabetic neuropathy;fusing shape information in lung segmentation in chest radiographs;structural similarity-based approximation of signals and images using orthogonal bases;a neighborhood dependent nonlinear technique for color image enhancement;image segmentation for robots: fast self-adapting Gaussian mixture model;incremental hybrid approach for unsupervised classification: applications to visual landmarks recognition;on-board monocular vision system pose estimation through a dense optical flow;and a geometric data structure applicable to image mining and retrieval.
the proceedings contain 90 papers. the topics discussed include: automated vertebra identification from X-ray images;towards non invasive diagnosis of scoliosis using semi-supervised learning approach;articulated mode...
ISBN:
(纸本)3642137717
the proceedings contain 90 papers. the topics discussed include: automated vertebra identification from X-ray images;towards non invasive diagnosis of scoliosis using semi-supervised learning approach;articulated model registration of MRI/X-ray spine data;multimodality image alignment using information-theoretic approach;retinal images: optic disk localization and detection;automatic corneal nerves recognition for earlier diagnosis and follow-up of diabetic neuropathy;fusing shape information in lung segmentation in chest radiographs;structural similarity-based approximation of signals and images using orthogonal bases;a neighborhood dependent nonlinear technique for color image enhancement;image segmentation for robots: fast self-adapting Gaussian mixture model;incremental hybrid approach for unsupervised classification: applications to visual landmarks recognition;on-board monocular vision system pose estimation through a dense optical flow;and a geometric data structure applicable to image mining and retrieval.
the proceedings contain 21 papers. the topics discussed include: deep learning based image detection model for pavement cracks and potholes;improvement of face detection accuracy for blurred mask wearers;detecting pha...
ISBN:
(纸本)9798400709586
the proceedings contain 21 papers. the topics discussed include: deep learning based image detection model for pavement cracks and potholes;improvement of face detection accuracy for blurred mask wearers;detecting phagocytotic activity of leukocytes in gram stained smears images;progressive enhancement of anatomical structural and medical feature learning for cephalometric landmark detection;vision transformer for audio-based depression detection on multi-lingual audio data;revolutionizing medical diagnostics: cutting-edge image detection and recognition techniques;adaptive weighted-rosette trajectories based on sparse models and nuclear norm regularization for fast MRI restoration;and predicting yeast-like fungi from gram stained smears images.
the proceedings contain 30 papers. the topics discussed include: a novel K-means clustering under bi-partition of feature set;data analytics in agile project management;public perception on ‘Hong Kong and Macao Vehic...
ISBN:
(纸本)9798400717567
the proceedings contain 30 papers. the topics discussed include: a novel K-means clustering under bi-partition of feature set;data analytics in agile project management;public perception on ‘Hong Kong and Macao Vehicles Going North’: text mining on Sina Weibo;data-driven study of UK terrorism: a K-prototypes clustering analysis of the UK’s terrorist incidents;Medusa ransomware against data privacy: a comprehensive study on ransomware attacks across various organizations and strategic recommendations for future prevention;cryptojacking: a comprehensive review of attack techniques, victims, and effective mitigation strategies;business email compromise: a comprehensive taxonomy for detection and prevention;and examining neural networks through architectural variation analysis for image classification.
A capsule is a group of neurons whose activity vector models different properties of the same entity. this paper extends the capsule to a generative version, named variational capsules (VCs). Each VC produces a latent...
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ISBN:
(纸本)9789819786916;9789819786923
A capsule is a group of neurons whose activity vector models different properties of the same entity. this paper extends the capsule to a generative version, named variational capsules (VCs). Each VC produces a latent variable for a specific entity, making it possible to integrate imageanalysis and image synthesis into a unified framework. Variational capsules model an image as a composition of entities in a probabilistic model. Different capsules divergence with a specific prior distribution represents the presence of different entities, which can be applied in imageanalysis tasks such as classification. In addition, variational capsules encode multiple entities in a semantically-disentangling way. Diverse instantiations of capsules are related to various properties of the same entity, making it easy to generate diverse samples with fine-grained semantic attributes. Extensive experiments demonstrate that deep networks designed with variational capsules can not only achieve promising performance on imageanalysis tasks (including image classification and attribute prediction) but can also improve the diversity and controllability of image synthesis.
As computer vision and imageanalysis technologies rapidly mature, they can revolutionize medical imaging, ushering in a new era of precision in diagnosis and treatment. In this research study, we explore innovative m...
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this paper presents a method for examining neural networks in image classification through architectural variation analysis. Small-scale experiments generate initial insights, and the configurations are further tested...
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Emotion recognition is expected to play a critical role in improving user experiences for digital products in the near future. In this context, most of the past work has emphasized on emotion recognitionthrough image...
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this research investigation explores the transformative potential of deep learning, particularly Convolutional Neural Networks (CNN) with U-Net architectures, in revolutionizing medical diagnostics through image detec...
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this study explores the potential of utilizing Facial Expression Activations (FEAs) captured via the Meta Quest Pro Virtual Reality (VR) headset for Facial Expression recognition (FER) in VR settings. Leveraging the E...
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