Roads are viewed as the fundamental method of transportation. Nonetheless, because of the substantial gridlock, these roads require framework upkeep. Frequently this support isn't done on the grounds that it is di...
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Eye coloboma is a type of congenital eye abnormality that causes developmental abnormalities of the eye which may culminate in eye disorders that fundamentally derange eyesight. Fractional and timely diagnosis remains...
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ISBN:
(数字)9798331508845
ISBN:
(纸本)9798331508852
Eye coloboma is a type of congenital eye abnormality that causes developmental abnormalities of the eye which may culminate in eye disorders that fundamentally derange eyesight. Fractional and timely diagnosis remains highly important to its proper managing and treating. This work proposes a model with a Transformer-Enhanced U-Net design implemented with Transfer Learning to enhance the ability of the model to detect and segment eye coloboma from medical imaging data. This work builds upon the benefits of U-Net which has shown promising results especially in the biomedical image segmentation problem through addition of transformer modules that introduce long range dependencies and contextual information. This enhancement makes helps the model to pay more attention to such minor aspects as coloboma and general diagnostic accuracy consequently. Thanks to Transfer Learning with a pretrained backbone, for example Efficient Net the system is provided with Feature Representations recovered from large datasets that are already available and training time is drastically cut short while the performance of the system is not compromised at *** approach includes fine-tuning of Transformer-Enhanced U-Net model using a selected set of eye images, labelled for coloboma existence. By including the self-attention mechanism, the model is capable of focusing on the critical regions in the image, increasing its responsiveness to any form of coloboma. Preliminary tests show that this scheme performs better than the standard convolutional networks for segmenting complex regions by minimizing false negatives. Further, the model’s flexibility to different imaging conditions demonstrates its suitability in realistic clinical applications. The objective of this research is to come up with a dependable, Auto-Generated diagnostic tool that will help the ophthalmologists in the early diagnosis of the eye related illnesses hence making increased positive outcomes for eye patients. The Transf
Automatic short answer grading (ASAG) techniques have been shown to cut down on the time and work needed to grade exams, and it is a method that is becoming more and more common, especially with the rise in popularity...
Automatic short answer grading (ASAG) techniques have been shown to cut down on the time and work needed to grade exams, and it is a method that is becoming more and more common, especially with the rise in popularity of online courses. This study compares the results of 7 pre-trained embedding models using just one feature to automatically grade brief responses: the similarity between the model answer's and the student answer's embeddings. Regression models are developed and evaluated to predict a short answer's score based on the similarities between all pairs of answers in the Mohler dataset. The predictions are evaluated by comparing the Root Mean Squared Error (RMSE) and Pearson correlation scores of each model.
In medical image processing, categorizing brain tumors is one of the most critical and challenging challenges that must be solved. Because manual classification carried out with the assistance of humans often leads to...
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Precise prediction of anti-cancer drug responses has become a crucial obstruction in anti-cancer drug design and clinical applications. In recent years, various deep learning methods have been applied to drug response...
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In the dynamic landscape of web development, the judicious choice of platform and structure plays a pivotal role. This comprehensive study conducts a thorough comparison of four prominent web development technologies:...
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Communication is the key behind the whole human evolution, and there would be nothing possible if the stream for communicating our thoughts to one another were cut off. Language is a significant factor when it comes t...
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Communication is the key behind the whole human evolution, and there would be nothing possible if the stream for communicating our thoughts to one another were cut off. Language is a significant factor when it comes to conveying one's ideas, thoughts, and information to other people. Sign language is used to communicate hard-of-hearing people's opinions. Every country has different sign languages. In this paper, we have used ISL (Indian Sign Language). To ease communication between ordinary people and deaf/dumb people, we propose the design and implementation of a model that translates a live voice, audio recordings, or text of a native Indian regional language (Tamil) to text and then further matches it to sign language animations from the video animation dataset. The speech is converted to text using two deep learning models LSTM(Long Short Term Memory), Bi-LSTM, and Google API. Then the text is transformed into a sign using ISL (Indian Sign Language) dataset. The proposed models achieved 45%, 65%, and 95% accuracy for LSTM, Bi-LSTM, and Google API, respectively.
The congestion in the Flying Ad hoc Network (FANET) is due to insufficient bandwidth or a heavy load on the network. The multipath routing protocol AOMDV (Ad -hoc On-demand Distance Vector) is used for balance the loa...
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The necessity for computer networks' use is expanding quickly, which raises problems with preserving network secrecy, availability, and integrity. Intrusion can be defined as an intentional breach of security rule...
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Collaborative learning has recently become more common in educational settings and has the potential to revolutionise the way students are taught today. Pair programming is a tool for group learning in which two progr...
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