Titlebook: Image Analysis and Processing – ICIAP 2023; 22nd International C Gian Luca Foresti,Andrea Fusiello,Edwin Hancock Conference proceedings 202

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Ahmed Tabia,Fabien Bonardi,Samia Bouchafahe clinical diagnosis and management of pediatric leukemia and will prove invaluable to specialists, generalists, and trainees alike.978-3-642-42370-3978-3-642-13781-5Series ISSN 1613-5318 Series E-ISSN 2191-0812

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Image Retrieval in Semiconductor Manufacturing,ueried e.g. for quality inspection purposes. In this work we design an image retrieval solution over IMAGO, a dataset of Transmission Electron Microscopy (TEM) images of nano-sized silicon structures collected in the production site of STMicroelectronics, in Agrate Brianza, Italy. Image retrieval in

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,Self-Similarity Block for Deep Image Denoising,age denoising ignored NLSS and were made of a sequence of convolutional layers trained to suppress noise. The first denoising CNNs leveraging NLSS prior were performing non-learnable operations outside the network. Then, pre-defined similarity measures were introduced and finally learnable, but scal

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,Shallow Camera Pipeline for Night Photography Enhancement,sults, their high computational requirements and limited interpretability can pose challenges. To address these limitations, we propose a camera pipeline for rendering visually pleasing photographs in low-light conditions. Our approach is characterized by a shallow structure, explainable steps, and

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,GCK-Maps: A Scene Unbiased Representation for Efficient Human Action Recognition,include deep-learning approaches based on RGB videos and pre-computed optical flow maps. Recently, 3D Gray-Code Kernels projections have been assessed as an alternative way of representing motion, being able to efficiently capture space-time structures. In this work, we investigate the use of GCK po

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,Autism Spectrum Disorder Identification from Visual Exploration of Images,rent gaze patterns from healthy controls in visual exploration of images and semantic interpretation, these are promising biomarkers to exploit in diagnosis. This study aims at developing a model to assist in the diagnosis of ASD using gaze data when static images are presented to the subjects. We f

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Target-Driven One-Shot Unsupervised Domain Adaptation,a target domain with only a single unlabeled target sample. Unlike existing approaches that rely on large labeled source and unlabeled target data, our Target-Driven One-Shot UDA (TOS-UDA) approach employs a learnable augmentation strategy guided by the target sample’s style to align the source dist