The recognition of license plates, known as Automatic Number Plate recognition (ANPR), is an important topic in the fields of smart transportation systems and imagerecognition. ANPR has the potential to significantly...
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Most computer vision and machinelearning-based approaches for historical document analysis are tailored to grayscale or RGB images and thus, mostly exploit their spatial information. Multi-spectral (MS) and hyperspec...
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ISBN:
(纸本)9783031133213;9783031133206
Most computer vision and machinelearning-based approaches for historical document analysis are tailored to grayscale or RGB images and thus, mostly exploit their spatial information. Multi-spectral (MS) and hyperspectral (HS) images contain, next to the spatial information, a much richer spectral information than RGB images (usually spreading beyond the visible spectral range) that can facilitate more effective feature extraction, more accurate classification and recognition, and thus, improved analysis. Although utilization of a rich spectral information can improve historical document analysis tremendously, there are still some potential limitations of HS imagery such as camera induced noise and blur that require a carefully designed preprocessingstep. Here, we propose a novel blind HS image deblurring method tailored to document images. We exploit a low-rank property of HS images (i.e., by projecting a HS image to a lower dimensional subspace) and utilize a text tailor image prior to performing a PSF estimation and deblurring of subspace components. The preliminary results show that the proposed approach gives good results over all spectral bands, removing successfully image artefacts introduced by blur and noise and significantly increasing the number of bands that can be used in further analysis.
Diabetes mellitus is a condition that occurs when the glucose level in the blood goes high. The eye-related issues due to diabetes may include diabetic retinopathy and diabetic maculopathy. It also includes conditions...
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Diabetes mellitus is a condition that occurs when the glucose level in the blood goes high. The eye-related issues due to diabetes may include diabetic retinopathy and diabetic maculopathy. It also includes conditions such as Glaucoma and Cataracts. All these conditions can steer toward poor vision and blindness. Artificial intelligence (AI) is the latest methodology used for eye image analysis. It is all about intelligent programming with the help of intelligent algorithms that make intelligent machines do what a human does. machinelearning and deep learning techniques are subtypes of AI. In this paper, we have summarized the findings of studies that have detected diabetic retinopathy and diabetic maculopathy using various AI methods.
The skin is the organ that protects the human body. However, factors such as solar radiation damage the texture and skin cells. Sometimes, the lack of timely diagnosis leads to skin cancer. In this line, melanoma is t...
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ISBN:
(纸本)9781665455176
The skin is the organ that protects the human body. However, factors such as solar radiation damage the texture and skin cells. Sometimes, the lack of timely diagnosis leads to skin cancer. In this line, melanoma is the most dangerous type of cancer and has caused the greatest number of deaths related to skin diseases. With this problem, collaborative efforts between different research areas are necessary to support early detection of the disease. In this way, the evolution of algorithms based on neural networks plays an important role for imageprocessing, which is an essential activity for pattern detection and recognition in medical diagnosis. Faced with this challenge, this research proposes a web prototype based on convolutional neural networks to support melanoma detection. In this context, the reference framework suggested by the Cross Industry standard Process for Data Mining (CRISP-DM) was used. For this, 18,000 high-quality images were compiled from the data science community. In addition, two learning models (based on convolutional neural network and Res-Net50) were created and evaluated. With these premises, a web application was developed using the waterfall model. Finally, conclusions and future work are suggested at the end of the document.
In recent years, progress in machinelearning methods has greatly influenced the creation of assistive technologies designed to enhance the quality of life for individuals with visual impairments. This paper introduce...
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ISBN:
(数字)9798350367720
ISBN:
(纸本)9798350367737
In recent years, progress in machinelearning methods has greatly influenced the creation of assistive technologies designed to enhance the quality of life for individuals with visual impairments. This paper introduces a unique real-time image analysis method specifically developed for the visually impaired community. Leveraging the You Only Look Once (YOLO) dataset and machinelearning algorithms implemented in Python, our The suggested system provides a seamless and efficient solution for identifying objects in the circumventing environment in genuine-time. In this study, we performed comprehensive experiments to assess the effectiveness of our system, taking into account aspects like detection accuracy, processing speed, and usability for users with visual impairments. The results demonstrate the efficacy and reliability of our approach in genuine-world scenarios, showcasing its potential to be accommodated as a valuable and implement for improving autonomy and mobility of visually impaired individuals.
The proceedings contain 17 papers. The topics discussed include: predicting the impact of type changes on overall equipment effectiveness (OEE) through machinelearning;technical feasibility and design challenges of u...
ISBN:
(纸本)9781665499651
The proceedings contain 17 papers. The topics discussed include: predicting the impact of type changes on overall equipment effectiveness (OEE) through machinelearning;technical feasibility and design challenges of unmanned aerial vehicle based drive testing on cellular networks;tensor-based format for exchanging hypergraphs between cognitive entities;recommendations on electromagnetic compatibility testing of unmanned aerial vehicles;a mobile application for training echolocation with a novel method for spatially rendered echoes;outlines of a graph-tensor based adaptive associative search model for Internet of digital reality applications;accessibility evaluation of healthcare webpages in Hungary using accessibility barrier computation algorithm;handheld 3D scanning and imageprocessing for printing body parts - a workflow concept and current results;and defining synergies between robotics, cognitive infocommunications and internet of digital reality.
This research paper introduces a Python-based implementation of a facial recognition system utilizing face recognition and Open CV libraries. The system has diverse applications, including security, surveillance, soci...
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The ability to recognise and interpret emotional expressions is crucial since emotions play a significant role in our daily lives. Emotions are multifaceted phenomena that affect our behavior, perception, and cognitio...
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Deep learning success in a wide range of applications, such as imagerecognition and natural language processing, has led to the increasing usage of this technology in many domains, including safety-critical applicati...
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There have been countless advancements in medical research, and a wide variety of diagnostic procedures for human body problems have been developed. Pathological testing, on the other hand, is time-consuming, painful,...
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