In this paper, a multi-feature detection method based on graph cut for photovoltaic panels is proposed. Combined with multi-dimensional features such as optical flow field and light intensity, an interactive feature r...
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A fundus image is a two-dimensional pictorial representation of the membrane at the rear of the eye that consists of blood vessels, the optical disc, optical cup, macula, and fovea. Ophthalmologists use it during eye ...
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A fundus image is a two-dimensional pictorial representation of the membrane at the rear of the eye that consists of blood vessels, the optical disc, optical cup, macula, and fovea. Ophthalmologists use it during eye examinations to screen, diagnose, and monitor the progress of retinal diseases or conditions such as diabetes, age-marked degeneration (AMD), glaucoma, retinopathy of prematurity (ROP), and many more ocular ailments. Developments in ocular optical systems, image acquisition, processing, and management techniques over the past few years have contributed to the use of fundus images to monitor eye conditions and other related health complications. This review summarizes the various state-of-the-art technologies related to the fundus imaging device, analysis techniques, and their potential applications for ocular diseases such as diabetic retinopathy, glaucoma, AMD, cataracts, and ROP. We also present potential opportunities for fundus imaging-based affordable, noninvasive devices for scanning, monitoring, and predicting ocular health conditions and providing other physiological information, for example, heart rate (HR), blood components, pulse rate, heart rate variability (HRv), retinal blood perfusion, and more. In addition, we present different types of technological, economical, and sociological factors that impact the growth of the fundus imaging-based technologies for health monitoring.
Multimodal medical image fusion is vital for extracting complementary information and generating comprehensive images in clinical applications. However, existing deep learning-based fusion approaches face challenges i...
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To enable real-time monitoring of fire operations within construction sites and to reduce the chance of fires, this paper proposes a detection algorithm that incorporates target recognition and imageprocessing. First...
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The proceedings contain 69 papers. The special focus in this conference is on Recent Trends in machine Learning. The topics include: Implementation of Dual-Band Dielectric Resonator Antenna for 5G applications;defect ...
ISBN:
(纸本)9789819994410
The proceedings contain 69 papers. The special focus in this conference is on Recent Trends in machine Learning. The topics include: Implementation of Dual-Band Dielectric Resonator Antenna for 5G applications;defect Detection in Metal Surfaces Using Computer vision;liver Cirrhosis Prediction Using machine Learning Classification Techniques;a Recent Survey on Risk Factors Affecting the Blood Pressure in India;Real-Time Monitoring System for Breakdown Analysis and OEE in the Wire Drawing Industry;tooth Sensitivity Device—Detection and Diagnosing of Sensitivity in the Dental Pulp;recognition of Skin Cancer;ioT-Based Smart Street Lighting Surveillance System;rock Segmentation of Real Martian Scenes Using Dual Attention Mechanism-Based U-Net;IAAS: IoT-Based Automatic Attendance System with Photo Face Recognition in Smart Campus;hardware Implementation of Moving Object Detection Using Background Subtraction Algorithm;crime Pattern Identification and Prediction Using machine Learning;IMICE: An Improved Missing Data Imputation Using machine Learning;analyzing Students’ Opinion on E-Learning—Indian Students’ Perspective;rash Driving Detection and Alerting System;Logistic-Based OvA-CNN Model for Alzheimer’s Disease Detection and Prediction Using MR images;Comparative Study of CNNs for Camouflaged Object Detection;3D Avatar Reconstruction Using Multi-level Pixel-Aligned Implicit Function;Helmet Detection Using YOLO-v5 and Paddle OCR for Embedded Systems;defogNet: A Residual Network for Removal of Fog Using Weighted Combination Loss;Text-to-image Generation Model with DNN Architecture and Computer vision for Embedded Devices Using Quantization Technique;one-Shot Learning for Archaeological Site Data Using Deep Neural Network on Embedded Systems;enhanceNet: A Deep Neural Network for Low-Light image Enhancement with image Restoration;intelligent Prediction of Cardiac Abnormality.
Actions speak more than words. In the context of the above statement, the importance of gestures and using them to control a system has become popular. The hand gesture recognition system for opening applications in W...
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In the field of computer vision, detecting tiny objects in remote sensing images has long been a challenging task. This difficulty primarily stems from the poor matching of tiny objects with specific feature scales, c...
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In this paper, we introduce an interactive multimodal vision-based robot teaching method. Here, a multimodal 3D image (color (RGB), thermal (T) and point cloud (3D)) was used to capture the temperature, texture and ge...
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The primary problem facing agriculture, which is essential to ensuring the world's food security, is maximizing crop productivity while reducing the effects of plant diseases. Advanced technologies have the potent...
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Picture processing is applied in all kind of fields, such as space science research, medical imaging, photography art. Because the human vision system is a complex nonlinear dynamic system, the traditional image enhan...
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