3 天前 - … based cognitive states classification, each providing unique feature extraction and
learning … , personalized learning, user interface design, and mental health interventions. As …

3 天前 - … (GNN) to classify the public health, urban microclimate, … method using reference
photos and a deep learning model … section, For feature extraction, the pre-processed data are …

3 天前 - … Image categorization, object recognition, and feature extraction … Deep Learning will
eventually surpass machine learning. … to medical picture analysis has emerged using deep …

3 天前 - … focuses on feature extraction techniques tailored specifically for blockchain data.
These … applications in domains such as finance, supply chain management, and healthcare. …

3 天前 - … feature extraction from medical … deep learning framework of CNN and long
short-term memory is proposed in this research for classifying and predicting brain tumors using …

4 天前 - … appliances, and faulty operation of medical equipment. There are numerous techniques
… methodology for feature extraction and machine learning techniques to classify the PQ …

4 天前 - … Comparisons are made between the outcomes achieved by classical machine
learning … of each feature subset and analyze the contribution of individual features within the …

5 天前 - … OBJECTIVES: Magnetic Resonance Imaging (MRI) has emerged as a valuable
medical … , deep learning approaches offer the advantage of automating feature extraction …

5 天前 - … A machine learning tool using natural language … the automated extraction of operation
information from medical … on clinical data warehouses to automate information extraction …

5 天前 - … learning faces challenges due to its lack of easy and fast interpretability and … on
ECG features and time series data respectively. Our findings reveal that features extracted from …