Fetal health care is vital in ensuring the health of pregnant women and the *** check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential *** know the status of t...
详细信息
Fetal health care is vital in ensuring the health of pregnant women and the *** check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential *** know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,***,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during *** researchers have proposed various methods for classifying the status of fetus *** processing of CTG data is time-consuming and ***,automated tools should be used to classify fetal *** study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal *** strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also *** study easily provides valuable interpretations for healthcare professionals in the decision-making process.
In the field of computer vision and pattern recognition,knowledge based on images of human activity has gained popularity as a research *** recognition is the process of determining human behavior based on an *** impl...
详细信息
In the field of computer vision and pattern recognition,knowledge based on images of human activity has gained popularity as a research *** recognition is the process of determining human behavior based on an *** implemented an Extended Kalman filter to create an activity recognition system *** proposed method applies an HSI color transformation in its initial stages to improve the clarity of the frame of the *** minimize noise,we use Gaussian *** of silhouette using the statistical *** use Binary Robust Invariant Scalable Keypoints(BRISK)and SIFT for feature *** next step is to perform feature discrimination using Gray *** that,the features are input into the Extended Kalman filter and classified into relevant human activities according to their definitive *** experimental procedure uses the SUB-Interaction and HMDB51 datasets to a 0.88%and 0.86%recognition rate.
The detection of cyberattacks has been increasingly emphasized in recent years, focusing on both infrastructure and people. Conventional security measures such as intrusion detection, firewalls, and encryption are ins...
详细信息
Products that are counterfeit pose a serious threat to both consumers and businesses. Our suggested method makes use of blockchain technology to establish an open and trustworthy platform for tracking phone goods all ...
详细信息
In a flipped and adaptive learning environment, adaptability in time is the key to handling constant change and student individuality for their success. To maximize the learning experience, an urgently demanding task ...
详细信息
ISBN:
(纸本)9798350336429
In a flipped and adaptive learning environment, adaptability in time is the key to handling constant change and student individuality for their success. To maximize the learning experience, an urgently demanding task is to identify lower-performance students on the fly for targeted timely interventions. Existing state-of-the-art works focus on a regular course setting, where timelines in adaptability is not necessarily a high priority. These works apply batch-based (offline) learning algorithms or ensemble methods, which need the entire training data collected before prediction. These methods, without the whole learning process into consideration, may affect the accuracy of prediction results. In response to the urgent need, we propose to apply an online predictive learning method to handle incoming student data throughout the time steps of a course semester and predict low-performing students for each time step, with a goal to minimize the overall classification error. We built up our experimental design on the multiple learning theories, designed and executed four surveys, and conducted predictive analysis on student data. In the process of feature engineering, we conducted a series of correlation and cause-effect regression analyses and further quantified the determinant factors of predicting student performance. We further developed a framework for identifying low-performing students on the fly and comparing and analyzing deep online learning and diverse traditional batch-based (offline) predictive modeling methods. Our comparative analysis indicates that the online predictive learning approach is encouraging. It outperforms all batch-based (offline) methods overall;prediction results on low-performing students at a time step help identify their problem patterns situated in the context of the whole course progress to design and conduct timely interventions. The innovative study set up a stage for us to deeply understand the learning process, identify main determ
Handwritten character recognition falls under the domain of image classification, which has been under research for years. But still, specific gaps need to be highlighted as offline handwritten character recognition (...
详细信息
In recent years, the Internet of Things (IoT) has grown at an exponential rate, transforming the healthcare business and perhaps leading to the creation of healthcare big data. As a result, there is a requirement to s...
详细信息
The paper uses the SOAR analysis paradigm to investigate the impact of Large Language Models (LLMs) such as ChatGPT on crucial healthcare industry stakeholders. The background of the study highlights the growing appli...
详细信息
Agriculture plays an important role, in Indias economy providing support to a portion of the population and contributing significantly to the GDP. It is crucial to predict crop yields in order to make decisions and pr...
详细信息
Background: The automated classification of videos through artificial neural networks is addressed in this work. To explore the concepts and measure the results, the data set UCF101 is used, consisting of video clips ...
详细信息
暂无评论