A condition affecting the heart with blood vessels is called Cardio Vascular Disease (CVD). It is the main reason for death. Early detection can help prevent or lessen it, which lowers mortality. Various study article...
A condition affecting the heart with blood vessels is called Cardio Vascular Disease (CVD). It is the main reason for death. Early detection can help prevent or lessen it, which lowers mortality. Various study articles describe the application of algorithmic machine learning to identify cardiac diseases. When the algorithm is applied to the dataset’s records, a faster and more precise prediction of cardiovascular illnesswill enable the patient to receive therapy. Cardiologists can make judgments quickly with the aid of these projections. The suggested study employs self-defined Decision Tree, random forest, Logistic Regressions, Support Vector Machine (SVM), grid search to identify the presenceof cardiovascular illness. We examine and assess its performance to forecast it.
The classification of mango leaf diseases is critical for effective disease management and ensuring high-quality yields in mango cultivation. This paper presents a comprehensive study on using deep learning techniques...
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Nowadays, road accidents occur owing to the distractions of people who drives the vehicles by Internal or External factors. Using of Mobile phones and driving continuously for several hours are some of the reasons of ...
Nowadays, road accidents occur owing to the distractions of people who drives the vehicles by Internal or External factors. Using of Mobile phones and driving continuously for several hours are some of the reasons of driver distraction. Among these, the main distractions faced by drivers are drowsiness. Specifically, a driver turns to sleep while driving causes an accident. Latest studies reveal that approximately 20% of vehicle hits have caused by drowsy drivers. And now, these types of accidents can be detected by using modern software technologies. In that, Deep learning is a category of Artificial Intelligence (AI) concepts, which imitate the way humans, gain certain types of knowledge. Deep Learning plays a vital role in health care industry also. The main characteristic of deep learning is, it can built a model automatically by self-learning. In deep learning, Convolutional Neural Network (CNN) is a type of deep neural networks, which is applied to investigate visual imagery. In this research work, a CNN model will be built to identify the drowsiness of the driver by observing the driver's face reactions. The driver drowsiness dataset is downloaded from data-flair website and trained with CNN architecture. In this work, an image of driver's face will be captured through web camera and compared with trained images .If matches occur, an alarm will be given to make awareness to the driver and to avoid accidents.
The classification of mango leaf diseases is critical for effective disease management and ensuring high-quality yields in mango cultivation. This paper presents a comprehensive study on using deep learning techniques...
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ISBN:
(数字)9798331505790
ISBN:
(纸本)9798331505806
The classification of mango leaf diseases is critical for effective disease management and ensuring high-quality yields in mango cultivation. This paper presents a comprehensive study on using deep learning techniques to classify various mango leaf diseases, leveraging convolutional neural networks (CNNs) and hybrid models. A total of 7,524 images were used in our study. These included 4,000 training samples and 3,524 testing samples. The images were split into eight groups, which were powdery mildew, cutting weevil, anthracnose, bacterial canker, sooty mold, gall midge, healthy, and die back. The suggested method starts with feature extraction using VGG19 and MobileNetB1, then classification using both standalone models (ResNet50V2 + EfficientNetB1 and VGG16 + MobileNetB1). We employed data augmentation techniques like random brightness adjustment, rotation, and flipping to enhance the robustness of the model. We conducted hyperparameter tuning using hyperband and Bayesian optimization to optimize the model’s performance. Experimental results demonstrate that the hybrid models achieved superior performance, with ResNet50V2 and EfficientNetB1 attaining a perfect accuracy of $100 \%$ on the test set. These findings highlight the potential of deep learning techniques to improve the accuracy and reliability of mango leaf disease diagnosis, contributing significantly to the advancement of precision agriculture.
For the successful business, several factors are considered and prediction is made for the sales of the product. Here, the sales prediction is proposed to forecast the sales of Rossamann stores using machine learning ...
For the successful business, several factors are considered and prediction is made for the sales of the product. Here, the sales prediction is proposed to forecast the sales of Rossamann stores using machine learning algorithms. Sales forecasting is done by analyzing customer purchasing behaviour and it plays an important role in modern business intelligence. Forecasting future sales demand is key to business and business planning activities. Forecasting helps business organizations to make improvements, to make changes to business plans and to provide a stock storage solution. Forecast is determined by the use of data or information from past works and the consideration of recognized feature in future. Sales forecasting plays a vital role in strategic planning and market strategy for every company to assess past and present sales statistics and predict potential results. Overall, accurate sales forecasting helps the company to run more productively and efficiently, to save money on forecasts or predictions. In the proposed study, the linear regression and logistic regression model are analyzed and Simple Linear Regression (SLR) and Multiple Linear Regression (MLR) are trained and tested for our dataset. The data is processed to select the features and extract those features. Accurate projections make it easier for the shop to boost demand growth and a higher degree of sales generation. It produces better prediction rate.
We show that a quantum spin system has an exact description by non-interacting fermions if its frustration graph is claw-free and contains a simplicial clique. The frustration graph of a spin model captures the pairwi...
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