The proceedings contain 94 papers. The topics discussed include: patterns and disorder in chaos: a nonlinear approach to improve image analysis;quantitative bioimage analysis: from cell to numbers;new strategies for i...
ISBN:
(纸本)9781479986354
The proceedings contain 94 papers. The topics discussed include: patterns and disorder in chaos: a nonlinear approach to improve image analysis;quantitative bioimage analysis: from cell to numbers;new strategies for interactive web-based visualization of cultural heritage imagery;solutions for development of an intelligent video surveillance system;credal human activity recognition based-HMM by combining hierarchical and temporal reasoning;human posture recognition by combining silhouette and infrared cast shadows;super-resolution of facial images in forensics scenarios;3D real-time human action recognition using a spline interpolation approach;tracking based sparse box proposal for time constraint detection in video stream;and a novel algorithm of lane detection with a variance of scenarios including curved and dashed lane marks.
The proceedings contain 105 papers. The topics discussed include: cephalometric landmarks localization based on histograms of oriented gradients;an imageprocessing technique to detecting retina layers;a language inde...
ISBN:
(纸本)9781424485949
The proceedings contain 105 papers. The topics discussed include: cephalometric landmarks localization based on histograms of oriented gradients;an imageprocessing technique to detecting retina layers;a language independent text segmentation technique based on naive Bayes classifier;an efficient skew detection of license plate images based on wavelet transform and principal component analysis;compression resistant multichannel color image watermarking;video cut detection using block based histogram differences in RGB color space;enhancement of color images in HOT domain with quantitative measurements using entropy and relative entropy;design and development of a DSP processor based reconfigurable hand gesture recognition system for realtime applications;and vehicle detection and classification based on morphological technique.
This investigation purpose a unique Dynamic Bio-Information image Recognition System (DBIRS) built for the real-time monitoring of cancer cell apoptosis produced by available medical therapy. Utilizing advances in mic...
详细信息
Medical imageprocessing is a critical field that supports early diagnosis and treatment planning for various diseases, including tumors. Tumors, if detected at an early stage, can significantly improve patient outcom...
详细信息
ISBN:
(数字)9798331512248
ISBN:
(纸本)9798331512255
Medical imageprocessing is a critical field that supports early diagnosis and treatment planning for various diseases, including tumors. Tumors, if detected at an early stage, can significantly improve patient outcomes. However, the complexity of medical imaging data, including noise, artifacts, and variations in tumor shapes and sizes, presents significant challenges. This research proposes an innovative framework, CNN-Extreme Learning Machine Hybrid Algorithm (CNELM-Hybrid). The framework leverages the feature extraction capabilities of Convolutional Neural Networks (CNN) and the ultra-fast classification efficiency of Extreme Learning Machine (ELM). CNELM-Hybrid integrates these techniques into a unified architecture, CNELM-Edge, to deliver a robust and scalable solution for real-time medical image analysis. Simulation analysis was carried out using performance metrics such as classification accuracy, processing speed, sensitivity and specificity. The results demonstrate that CNELM-Hybrid achieves superior performance and significantly reduced computational time. Furthermore, the hybrid model exhibited enhanced capability in handling complex and imbalanced datasets, which are common challenges in medical imageprocessing. These findings underscore the potential of CNELM-Hybrid in advancing tumor detection methodologies and its applicability in real-time clinical environments.
The proceedings contain 92 papers. The topics discussed include: towards change detection in bi-temporal images using evidential conflict;detection of moroccan coastal upwelling using the alpha blending fusion techniq...
ISBN:
(纸本)9781538652398
The proceedings contain 92 papers. The topics discussed include: towards change detection in bi-temporal images using evidential conflict;detection of moroccan coastal upwelling using the alpha blending fusion technique of sea surface chlorophyll images and sea surface temperature images;evidence theory data fusion-based method for cyber-attack detection;qualitative semantic spatio-temporal reasoning based on description logics for modeling dynamics of spatio-temporal objects in satellite images;a real-time emotion recognition system for disabled persons;a framework for big data driven product traceability system;and resolution of 2-D time domain electric field integral equation with RWG functions using novel mesh technique based on hexagonal mesh.
As one of the most important data sources in machine vision system, camera is facing increasingly strict requirements in video image acquisition, processing and transmission. Through the in-depth analysis of the devel...
详细信息
ISBN:
(纸本)9798400713880
As one of the most important data sources in machine vision system, camera is facing increasingly strict requirements in video image acquisition, processing and transmission. Through the in-depth analysis of the development trend of the camera, it can be clear that its main pursuit of three goals: improve video imageprocessing performance, reduce costs and enhance flexibility. However, most of the existing video processing platforms have problems such as low data processing efficiency and lack of real-time performance, which is difficult to meet the high performance requirements of modern cameras for video imageprocessing. Because of its high real-time performance, powerful computing power, high integration and flexibility, embedded system has become a promising direction to realize advanced video imageprocessing algorithms. With the embedded platform, the camera system can realize more efficient real-time data processing and higher quality video image output. In the current market, three high-performance embedded processors stand out, namely DSP, ASIC and FPGA. Among them, FPGA chip has become the ideal hardware platform for camera video imageprocessing with its parallel computing capability, rich interface resources and field programmable characteristics. Based on Anlogic EG4S20 FPGA platform, this paper realizes imageprocessing functions, including Bayer format to RGB conversion, gray world algorithm and perfect reflection algorithm. This research makes full use of the powerful computing power of FPGAs to demonstrate imageprocessing and enhancement techniques to address key performance challenges in camera systems.
With the development of urban underground spaces, ensuring the safety of operational subway tunnels poses significant challenges. Among these challenges, tunnel structural deformation and foreign object detection are ...
详细信息
The proceedings contain 35 papers. The topics discussed include: EczemaNet: a deep CNN-based eczema diseases classification;improving CNN-based colorization of B&W photographs;News2image: automated system of image...
ISBN:
(纸本)9781728175744
The proceedings contain 35 papers. The topics discussed include: EczemaNet: a deep CNN-based eczema diseases classification;improving CNN-based colorization of B&W photographs;News2image: automated system of image recommendation to news articles;binary view classification of echocardiograms of the heart using transfer learning;real-time object detection using deep learning for helping people with visual impairments;coconut disease prediction system using imageprocessing and deep learning techniques;emotion recognition on large video dataset based on convolutional feature extractor and recurrent neural network;handwritten recognition: a survey;image augmentation for deep learning based lesion classification from skin images;pedestrian detection and classification for autonomous train;and detection of microconidia in microscopy images of fusarium oxysporum f. sp. cubense using imageprocessing techniques and neural networks.
The proceedings contain 39 papers. The topics discussed include: optimization method of loop detection based on shadow compensation;realtime lane detection model based on lightweight;research on image detection algor...
ISBN:
(纸本)9781450389075
The proceedings contain 39 papers. The topics discussed include: optimization method of loop detection based on shadow compensation;realtime lane detection model based on lightweight;research on image detection algorithm based on improved retinanet;a study of student learning status classification based on the detection of key objects within the visual field;an outlier detection method based on symmetry and curvature threshold;research on adaptive object detection method of kernel correlation filtering;attention enhanced multi-patch deformable network for image deblurring;recaptured image forensics based on image illumination and texture features;and using temporal convolutional networks to enable action recognition for construction equipment.
The high computational cost of digital imageprocessing, requiring high-performance hardware and extensive resources, severely limits real-time applications. While advancements in algorithm design and GPU acceleration...
详细信息
ISBN:
(数字)9798331531850
ISBN:
(纸本)9798331531867
The high computational cost of digital imageprocessing, requiring high-performance hardware and extensive resources, severely limits real-time applications. While advancements in algorithm design and GPU acceleration have significantly improved efficiency, modern AI-driven applications such as large language models (LLMs), Generative AI (GenAI), medical imaging, autonomous vehicle perception, photography, advanced nano-scale semiconductor metrology, satellite image analysis, high-precision manufacturing, robotics, and real-time anomaly detection, still demand further optimization to reduce computational overhead and improve *** this paper, we introduce GPU-Accelerated Feature Extraction to enhance runtime and efficiency in edge-based simulations. Our approach leverages AI-driven clustering, grouping images with similar visual and pattern characteristics to enable adaptive tuning on a small subset before generalizing across the full dataset. This method achieves a 3.78× reduction in ***, rather than processing an entire image, we recognize and extract a single representative pattern or region of interest (ROI) per image, removing redundant data and background noise. This refinement results in an additional 1.74× runtime improvement, culminating in an overall 6.6× speed boost, enhancing Scalable real-time AI processing. We also demonstrated that with a similar runtime, the accuracy achieved is 2.5× *** solution, integrated into Calibre SEMSuite™, supports multicloud and real-time deployment for enhanced scalability, usability, and performance, providing users with a powerful tool for fully automated, AI-driven image classification, making high-throughput image review feasible even at the scale required for cutting-edge *** performance gains, this approach introduces autonomous data cleaning, anomaly detection and defect identification mechanism, allowing failed patterns and defective images to be identified without h
暂无评论