The proceedings contain 78 papers. The topics discussed include: a video anomaly detection framework based on multi-scale dynamic prototype unit;a new RCNN-RF for efficient and robust parking lot available detection;l...
ISBN:
(纸本)9781510682900
The proceedings contain 78 papers. The topics discussed include: a video anomaly detection framework based on multi-scale dynamic prototype unit;a new RCNN-RF for efficient and robust parking lot available detection;lightweight hand small target detection method based on improved YOLOv5s;an improved ViBe motion detection method VIA background refresh from content difference;BFETNet: a bitemporal feature enhancement transformer network for remote sensing image change detection;obstacle detection method based on water reflection removal;LiDAR and hyperspectral remote sensing image fusion using extended extrema morphological profiles for semantic segmentation;enhanced medical image segmentation through hybrid attention and dynamic convolution networks;and research on apple leaf disease segmentation method based on improved U-Net.
The proceedings contain 21 papers. The topics discussed include: detecting cars and their states utilizing object detection;an application of head gesture for controlling electric wheelchair movement;major depressive ...
ISBN:
(纸本)9798400709425
The proceedings contain 21 papers. The topics discussed include: detecting cars and their states utilizing object detection;an application of head gesture for controlling electric wheelchair movement;major depressive disorder detection based on parallel spatiotemporal convolution network;high quality digital zoom using learning super-resolution;an improved reconstruction technique;software dependent image data compression using multiple encryption;using semi-automated annotation and optical character recognition for transcription of patient monitors using smartphone camera;leaf shape recognition using Fourier descriptors and Hough transform and classification using probabilistic neural network;non-intrusive people counting and identification simultaneously with commodity Wi-Fi devices;and using deep learning and adaptive window adjustment to facilitate the detection of pulmonary edema detection in chest x-rays: improving diagnostic accuracy and precision through advanced deep learning techniques.
The proceedings contain 137 papers. The topics discussed include: stochastic recursive gradient descent optimization-based on foreground features of fisher vector;an evaluation method of aggregate morphological charac...
ISBN:
(纸本)9781510657564
The proceedings contain 137 papers. The topics discussed include: stochastic recursive gradient descent optimization-based on foreground features of fisher vector;an evaluation method of aggregate morphological characteristics based on two-dimensional digitalimage technique;semantic segmentation of road scene based on multi-scale feature extraction and deep supervision;dynamic spectral–spatial multiscale feature extraction network for hyperspectral image classification;an improved approach for two-stage detection model;multi-task model for human pose estimation and person detection;ship detection in optical remote sensing images based on saliency and rotation-invariant feature;a defect detection method for plastic gears based on deep learning and machine vision;face tampering detection based on spatiotemporal attention residual network;and using Sentinel-2 imagery for detecting oil spills via spatial roughness of mixed normalized difference index.
digital signal processing has significantly impacted a variety of scientific and engineering domains, yet faces constraints such as complexity and power consumption, primarily attributed to analog-to-digital converter...
详细信息
ISBN:
(纸本)9798350377330;9798350377323
digital signal processing has significantly impacted a variety of scientific and engineering domains, yet faces constraints such as complexity and power consumption, primarily attributed to analog-to-digital converters. To address these challenges, optical analog computing has recently emerged as a promising solution. Recent advancements in flat optics devices unveil the potential for real time data processing with minimal power consumption and spatial footprint. To date, most achievements in analog signal processing have been realized through linear optics. Extending these capabilities to nonlinear optics offers even greater potential. Here, we demonstrate the synthesis of Volterra kernels with flat optics devices that leverage the inherent nonlocality of the nonlinear response. We delve into the potential applications of nonlinear nonlocal flat-optics, including nonlinear edge detection for imageprocessing and vector-vortex beam generation, pivotal in the fields of optical communications and optical sensing. We demonstrate the feasibility of nonlinear signal processing, as well as nonlinear spin-orbit coupling, in a very simple setup, made of a single thin film with second-order nonlinear susceptibility. Our findings contribute to the advancement of active, nonlinear, and quantum photonic devices, offering new avenues for signal processing and beam generation technologies.
With the development of the Internet, information carriers and communication methods have become diversified. As an important carrier for obtaining information, images are easily copied and tampered with during the co...
详细信息
Retinal optical Coherence Tomography (OCT) plays a pivotal role in diagnosing ocular disorders by providing detailed imaging of retinal layers. However, the analysis process remains time-consuming, posing a challenge ...
详细信息
ISBN:
(纸本)9781510679344;9781510679351
Retinal optical Coherence Tomography (OCT) plays a pivotal role in diagnosing ocular disorders by providing detailed imaging of retinal layers. However, the analysis process remains time-consuming, posing a challenge to its widespread use. This study investigates the integration of Artificial Intelligence (AI) to streamline the analysis of OCT images. Employing Deep Learning (DL) models-VGG16, ResNet18, DenseNet-transfer learning, and data augmentation, the research aims to enhance OCT images, optimize disease recognition, and accurately classify CNV (Choroidal Neovascularization), DME (Diabetic Macular Edema), DRUSEN, and NORMAL pathologies. The dataset undergoes preprocessing, resizing, and enhancement to refine the images. The DenseNet model achieved the highest test accuracy of 92.41% after 25 epochs, demonstrating its potential in efficiently diagnosing ocular pathologies through OCT images.
digitalimageprocessing, also known as computer imageprocessing, refers to the process of converting image signals into digital signals and processing them using computers. digitalimageprocessing first appeared in...
详细信息
With the continuous advancement of technology, array camera systems, serving as a collaborative system of multiple cameras, exhibit broad prospects in areas such as surveillance, imageprocessing, and computer vision....
详细信息
Near-eye light field displays are superior to conventional AR displays because they offer continuous focus and viewing experiences free from visual accommodation conflict (VAC). However, given a fixed number of pixels...
详细信息
ISBN:
(纸本)9798350349405;9798350349399
Near-eye light field displays are superior to conventional AR displays because they offer continuous focus and viewing experiences free from visual accommodation conflict (VAC). However, given a fixed number of pixels for representation of the spatio-angular information of a light field, the inherent tradeoff between angular and spatial resolutions presents a great challenge to the widespread adoption of light field technology. To address the challenge, we propose a hybrid super-resolution framework consisting of a digital neural network and an optical neural network and allowing an end-to-end optimization of the downsampling operation for fitting the light field data into a fixed-resolution display panel and the upsampling operation for enhancing the light field quality, all in the frequency domain. Experimental results show that the proposed hybrid framework is a promising approach to quality enhancement of near-eye light field displays.
This paper designs and applies a virtual simulation experimental teaching platform based on natural scene image recognition algorithms to enhance students' learning outcomes in the "digitalimageprocessing a...
详细信息
暂无评论