Electroencephalogram(EEG) signals are generally available in small limited quantities, and there are considerable variabilities between individual and recording sessions. Thus it is crucial to obtain a model capable o...
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Today’s era is the smart era where every person is trying to execute the process smartly. Then how the education system will be in a back place. The online conduction of courses either by engaging online classes or b...
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The availability of image editing software such as Adobe Photoshop or GIMP has made picture alteration so widespread these days. Finding these phony photos is a must for exposing image-based cyber crimes. Due to its u...
The availability of image editing software such as Adobe Photoshop or GIMP has made picture alteration so widespread these days. Finding these phony photos is a must for exposing image-based cyber crimes. Due to its ubiquity, images produced with a digital camera or smartphone are typically saved in the JPEG format. The 8×8 pixel-sized, independently compressed mage grids used by the JPEG technique are used. Images that haven't been altered have a comparable inaccuracy level. Due to a similar number of faults throughout the whole image, each block should degrade at roughly the same rate during resaving operations. Error Level Analysis was used to determine that the compression ratio of the false image was different from the actual images.
Metro-rail based rapid transport system is regarded as one of the prominent technology that can minimize the working hour wastage problem of a developed country due to traffic jams. However, to reap the benefits for b...
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Apart from the immediate use of Master cards and any form of electronic payment methods, money has been widely used for general exchange due to its usefulness. However, visually impaired people can suffer to know each...
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Metastatic cancer, characterized by the spread of cancer cells from the primary site to other parts of the body, poses significant diagnostic challenges. Accurate detection in histopathological images is crucial for e...
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ISBN:
(数字)9798331519094
ISBN:
(纸本)9798331519100
Metastatic cancer, characterized by the spread of cancer cells from the primary site to other parts of the body, poses significant diagnostic challenges. Accurate detection in histopathological images is crucial for effective patient management. In this study, we present a novel hybrid model combining ResNet50, self-attention mechanisms, and Gated Recurrent Units (GRUs) to enhance binary classification accuracy for metastatic cancer detection. Benchmarking against CNN-GRU, CNN-LSTM, and AlexNet-GRU models, our approach demonstrated superior performance on two datasets. For the Histopathologic Cancer Detection PCam Dataset, our model achieved 99.7% accuracy, 99.57% precision, 99.2% sensitivity, and 99.57% specificity. For the BreakHis Dataset, it attained 99.2% accuracy, 98.69% precision, 99.52% sensitivity, and 97.22% specificity. These results highlight our model’s potential to significantly reduce diagnostic errors and support pathologists in making more accurate diagnoses, outperforming existing models in the field.
This paper focuses of my enrollment in ICICS 2021 Competition Mowjaz Multi-Topic Labelling Task using Bidirectional Gated Recurrent Unit (Bi-GRU). The model is basically used to classify articles based on their topics...
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Since the evolution of the internet and accompanying services and technologies, people all over the world had started enjoying these developments, but unfortunately this wasn't without cost. On one side, companies...
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With the expansion of social media and advanced stages, the spread of fake news has ended up a noteworthy societal issue. This paper presents a comprehensive outline of machine learning strategies utilized for the det...
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ISBN:
(数字)9798331530389
ISBN:
(纸本)9798331530396
With the expansion of social media and advanced stages, the spread of fake news has ended up a noteworthy societal issue. This paper presents a comprehensive outline of machine learning strategies utilized for the detection of fake news. We talk about different approaches such as Natural Language Processing (NLP), unsupervised learning calculations, and machine learning models utilized within the recognizable proof of fake news. We dive into highlight designing, opinion investigation, and organize examination as key components of fake news detection frameworks. Moreover, we look at datasets, assessment measurements, and challenges related with detection of fake news. Through this analysis, we point to supply bits of knowledge into the current state-of-the-art techniques and headings for future investigate in combating fake news dispersal. This paper mainly used K-Nearest Neighbor, Jaccard similarity, LSTM, Decision Tree, and Logistic regression Classifiers for the classification. Main objective of this paper to verify the accuracy of models by performing the pre-processing the data and handle the imbalanced data more appropriately. The results of this papers show comparison of all classifiers with accuracy. Our results shows that KNN achieves 83%, 84% for Logistic Regression, 84% for Decision Tree, 85% for Jaccard Similarity & Random Forest is 85% and 98% for LSTM in our experiment.
Covid-19 has become one of the most dangerous diseases suddenly which is infecting the people in all over the world. It has created an impact on the lives of thousands of people all over the world. Governments of vari...
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