Histopathology and MRI produce different types of images and a single procedure to detect cancerous cells from both of them is considered tedious and time-consuming. Therefore, this study proposes a strategy that can ...
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In the current study, FloraNet was used to present an improved method for diagnosing leaf diseases in Sea Buckthorn. In the proposed model, Convolutional Neural Networks (CNN) and Random Forests (RF) are integrated. E...
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ISBN:
(数字)9798350361155
ISBN:
(纸本)9798350361162
In the current study, FloraNet was used to present an improved method for diagnosing leaf diseases in Sea Buckthorn. In the proposed model, Convolutional Neural Networks (CNN) and Random Forests (RF) are integrated. Essentially, CNN architecture is composed of a pair of convolutional layers, followed by a max-pooling layer; it is then followed by another pair of convolutional layers, before finishing off with a final pair of convolutional layers. Performance indicators such as Precision, Recall, F1-Score, or Accuracy are used to determine the performance of the model in terms of its performance. There were five disorders under investigation: Phakopsora, Erysiphe, Septoria, Colletotrichum, Phoma, as well as viral infections. Overall, the results show that the Micro Average accuracy for all classes is 95.11 %. According to the results, the individual accuracy ranges from 0.98 to 0.99 for each illness, while the F1-Scores range from 94.02% to 95.91% for each illness. This study concludes that the weighted average accuracy of 95.11 demonstrates a high level of proficiency of the model in identifying diseases, and indicates that the model is capable of identifying a wide variety of diseases. By using this integrated approach, agricultural scientists and researchers are able to detect Sea Buckthorn leaf diseases.
We introduce an application-specific c ircuit t hat c an b e programmed t o efficiently perform blind carrier phase recovery for different modulation formats. A circuit implementation that supports QPSK/16/32/64QAM is...
Rigorous simulations challenge recent claims that metalenses outperform conventional diffractive lenses, such as fresnel zone plates (FZPs), in focusing efficiency at high numerical apertures (NAs). Across various len...
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Rigorous simulations challenge recent claims that metalenses outperform conventional diffractive lenses, such as fresnel zone plates (FZPs), in focusing efficiency at high numerical apertures (NAs). Across various lens diameters, FZPs exhibit a pronounced asymmetry in the shadow effect, leading to significantly higher focusing efficiency when optimally oriented. Extending this analysis, we show that conventional blazed gratings also surpass meta-gratings in efficiency. Since any linear optical element can be decomposed into local gratings, these findings broadly underscore the superiority of blazed structures over binary metastructures. Experimental characterization of an FZP with a diameter = 3 mm, a focal length = 0.2 mm, operating at λ = 634 nm, confirms the dependence of efficiency on illumination direction. We attribute this sensitivity to the axial symmetry of the FZP geometry–a feature not present in the metalens. Our results emphasize the need for rigorous, direct comparisons between meta-optics and traditional diffractive optics to ensure accurate performance assessments.
In recent years, with the rapid development of the mobile Internet, it has become easier for users to read news and corresponding comments. Most people get used to reading news on-line. However, sociologists have show...
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As we scan the text images using digital photography devices like cameras, scanners etc. in general, there has always been an angle displacement occurs from the original axis of the text image. This skew of the image(...
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ISBN:
(数字)9798350367171
ISBN:
(纸本)9798350367188
As we scan the text images using digital photography devices like cameras, scanners etc. in general, there has always been an angle displacement occurs from the original axis of the text image. This skew of the image(s) often makes us uncomfortable to visualize the text in the image and even when we use such skewed text image with optical character reader, as it degrades the resulting accuracy. Therefore, skew detection and correction is the primary step to design a proper optical character reader, whose primary task is edge-detection and skew in text image using Hough transformation. The proposed algorithm is developed for detection the skew between -1° to +180° angle variation and it has been tested over 25000 distinct text images for testing and the state of the art accuracy is recorded $98.32 \%$ which is considerably better than existing methods.
The stage of software testing should be at the same degree of speed as development and software release, so the automation test is necessary to be aligned with other stages of the life cycle of development for softwar...
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In India, there are over 5 million deaf and mute people, with many cases going unreported. Communication can be difficult due to the lack of standardized sign language across the country. The Indian Sign Language (ISL...
In India, there are over 5 million deaf and mute people, with many cases going unreported. Communication can be difficult due to the lack of standardized sign language across the country. The Indian Sign Language (ISL) Detection project aims to improve communication by developing a system that can recognize and interpret ISL gestures. The system uses a type of artificial intelligence called machine learning, specifically Convo-lutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. These techniques help the system detect and classify ISL gestures from video input with high accuracy. The project has the potential to provide a more accessible means of communication for millions of deaf individuals in India.
"SignUp" is a web application designed to address the communication challenges faced by the deaf and mute community by providing a web application that allows real-time Indian Sign Language (ISL) recognition...
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ISBN:
(数字)9798331521691
ISBN:
(纸本)9798331521707
"SignUp" is a web application designed to address the communication challenges faced by the deaf and mute community by providing a web application that allows real-time Indian Sign Language (ISL) recognition and translation to facilitate communication between the deaf and dumb and the people who aren’t proficient in sign language. This research paper is focusing on the app’s real-time sign language recognition capabilities, text and speech output features, and the educational module for learning ISL.
In this paper, recognizing Arabic printed text is presented. A long time ago Recognizing the Arabic text has received great interest in information technology applications, as the Arabic language is among the differen...
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