UAVs have the advantages of efficient and automated inspection in life, and have important application value in industry, construction, energy and other fields. In this paper, an improved image recognition algorithm b...
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Diabetic retinopathy (DR), a severe complication arising from diabetes, poses a significant threat to vision due to the deterioration of retinal vessels. Recent techniques in DR detection, such as Convolutional Neural...
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ISBN:
(纸本)9798350391558;9798350379990
Diabetic retinopathy (DR), a severe complication arising from diabetes, poses a significant threat to vision due to the deterioration of retinal vessels. Recent techniques in DR detection, such as Convolutional Neural Networks (CNNs) and deep learning models, have shown promise but face challenges in accurately segmenting and classifying retinal images due to variations in image quality, occlusions, and the need for large annotated datasets. This study presents an innovative methodology for automated detection, grading, and segmentation of DR using deep learning, with a focus on residual encoder-decoder architecture. The study utilizes the Indian Diabetic Retinopathy imagedataset (IDRID), comprising 81 fundus images and labels, to rigorously evaluate the proposed methodology. By employing advanced image preprocessing techniques to enhance data quality, followed by a unified model capable of both segmentation and classification tasks, the proposed method achieves competitive performance metrics. Specifically, the model demonstrates an accuracy of 85.2% and specificity of 86.1% in segmenting and classifying DR features. These findings contribute to the improvement of diagnostic accuracy and patient outcomes in retinal diseases, offering potential applications in clinical settings to support early diagnosis and management of DR, thereby enhancing patient care and alleviating healthcare system burdens.
Underwater imaging is frequently challenged by light scattering, leading to haze, color distortion, and visibility loss. To address these issues, we introduce the AquaVision Dehaze and Enhancement algorithm to improve...
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image restoration is a very difficult task that always needs kernel knowledge beforehand, but blindly blurred images like camera-shake don't have any clue of the blur kernel or the original image. Restoring these ...
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The proceedings contain 75 papers. The topics discussed include: analysis of mental health disorders from survey reports using time series based linear regression;performance analysis of an energy efficient 1-bit hybr...
ISBN:
(纸本)9798350367461
The proceedings contain 75 papers. The topics discussed include: analysis of mental health disorders from survey reports using time series based linear regression;performance analysis of an energy efficient 1-bit hybrid full adder;KisanConnect: reshaping agricultural trade with dynamic pricing model;design of a 10-bit potentiometric DAC using Sky130nm technology using Xschem & Ngspice;quantum-dot cellular automata technology to implement digital circuits;advanced solar-powered oceanic environment monitoring buoy: real-time data for a sea conditions;real-time snake detection and recognition systems in videos using deep learning;a deep learning-based stream CipherGenerator for medical image encryption and decryption;image segmentation for MRI brain tumor detection using advance ai algorithm;and a comprehensive step of XAI for Bengali and English text detection and recognition from natural scene images.
In recent days, data transmission has increased a lot and they demand high security protocols for the safe transmission of data. Among the different types of data, images are sensitive as they could carry or represent...
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In response to the increasing demand in crowd management, and to solve the challenges of categorizing crowds as violent and non-violent, we have introduced a new architecture called Violent Behaviour Analysis (VBA). T...
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This research explores the transformative potential of integrating image fusion with the Internet of Things (IoT) in the field of smart healthcare. By combining multiple images from various sources, image fusion provi...
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ISBN:
(纸本)9798331540661;9798331540678
This research explores the transformative potential of integrating image fusion with the Internet of Things (IoT) in the field of smart healthcare. By combining multiple images from various sources, image fusion provides richer and more precise data, enhancing the capabilities of IoT devices. This synergy optimizes data quality and reliability in IoT systems, leading to improved diagnosis, patient monitoring, and telemedicine services in healthcare. The paper investigates the approaches and technologies used in combining image fusion with IoT, addressing challenges and limitations. Through case studies and current implementations, we highlight the transformative potential of this integration in creating smarter, more responsive, and efficient healthcare systems. Additionally, this study explores the implications for other sectors such as environmental monitoring, security, and smart cities.
Computer vision is a promising domain that focuses on emerging approaches, algorithms and technologies to provide computing capability to machine to analysis visual data, such as image files, videos files and real tim...
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Cashew kernel has rich nutritional value, cashew shell has very high industrial value, cashew shell is rich in cashew shell oil has high economic value of natural resources. However, cashews are suffering from pests a...
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