this paper focuses on the classification and recognition of Zhuang ethnic cultural landscape images using Convolutional Neural Network (CNN) technology. As an integral part of China's diverse ethnic culture, Zhuan...
详细信息
Sentiment Analysis plays a pivotal role in modern business operations, including analyzing and monitoring textual data. this paper presents a comparative analysis of various machine learning models for sentiment analy...
详细信息
ISBN:
(纸本)9798350354140;9798350354133
Sentiment Analysis plays a pivotal role in modern business operations, including analyzing and monitoring textual data. this paper presents a comparative analysis of various machine learning models for sentiment analysis of Twitter data. the models explored include Decision Tree, KNN classifier, Logistic Regression, Multinomial Naive Bayes, and Random Forest Classifier. Emphasizing the significance of preprocessing and vectorization techniques for feature extraction, the study delves into hyperparameter tuning to optimize each model's performance. Evaluation metrics such as accuracy, precision, recall, F1 score, and ROC analysis highlight the Random Forest Classifier demonstrating the highest accuracy. these findings underscore the efficacy of machine learning methodologies in sentiment analysis tasks and offer valuable insights for enhancing model performance in real-world applications.
Facial recognition technology plays a crucial role in various applications, from enhancing security at banks and organizations to streamlining attendance tracking in public gatherings and educational institutions. Tra...
详细信息
ISBN:
(纸本)9798350350661;9798350350654
Facial recognition technology plays a crucial role in various applications, from enhancing security at banks and organizations to streamlining attendance tracking in public gatherings and educational institutions. Traditional methods of attendance marking, such as signatures, names, and biometrics, can be time-consuming and error-prone. To address these challenges, a smart attendance system is proposed, leveraging Deep learning, Convolutional Neural Networks (CNN), and the OpenCV library in Python for efficient face detection and recognition. the system utilizes advanced algorithms, including Eigen faces and fisher faces, to recognize faces accurately. While deep learning models excel with large datasets, they may not perform optimally with few samples. By comparing input faces with images in the dataset, the system automatically updates recognized names and timestamps into a CSV file, which is then sent to the respective organization's head. Additionally, the system allows users to upload a single photo or a group photo, and it returns matched photos as output using a CNN. this feature enhances the system's flexibility and usability, providing users with a convenient way
the Knowledge-infused learning Workshop is a recurring event in ACM's KDD conferencethat gathers the research community on knowledge graphs and knowledge-enabled learning, grounded neurosymbolic AI, explainable a...
详细信息
ISBN:
(纸本)9798400704901
the Knowledge-infused learning Workshop is a recurring event in ACM's KDD conferencethat gathers the research community on knowledge graphs and knowledge-enabled learning, grounded neurosymbolic AI, explainable and safe AI, and applications in high-stakes decision-making problems. this year, the workshop aligned with Biden's vision of Responsible AI Development [1].
the ability of theoretical and monadic quantum models against number comparison to conventional Quantum Genetic Algorithm (QGA), quantitative particle swarm optimization, ant colony groups with simulated annealing typ...
详细信息
the proceedings contain 319 papers. the topics discussed include: optimization and empirical study on demonstration of smart city administrative system driven by big data;intelligent administrative decision support sy...
ISBN:
(纸本)9798350363586
the proceedings contain 319 papers. the topics discussed include: optimization and empirical study on demonstration of smart city administrative system driven by big data;intelligent administrative decision support system construction and efficiency evaluation based on big data analysis;application of gap technology in the secure cross-network transmission of civil aviation meteorological data;a multiple intertwined deep learning model for power grid data verification;a review of data leakage tracing models based on big data;research on evolutionary game theory of logistics information platform based on big data;big data-driven genetic algorithms for dynamic multi-drone route optimization;big data feature mining method for energy storage system of photovoltaic power station in typical scenarios;and image deblurring processing model combining spatial domain and frequency domain information.
the heart is a very important organ in the circulatory system. Heart disease is extremely severe and can even lead to death, therefore it is essential to make an accurate and timely diagnosis. However, health data ana...
详细信息
Withthe proposition of an integrated space-airground-sea communication network concept, satellites have become a key bridge connecting the globe. Low Earth Orbit (LEO) satellites, in particular, have become an import...
详细信息
ISBN:
(纸本)9798350362770;9798350362763
Withthe proposition of an integrated space-airground-sea communication network concept, satellites have become a key bridge connecting the globe. Low Earth Orbit (LEO) satellites, in particular, have become an important force in achieving global seamless communication due to their low latency and wide coverage advantages. LEO satellite networks can provide computing services to ground users under extreme conditions, which is of significant practical importance. the coordination among satellite edge nodes not only improves the utilization of space-based resources but is also key to enhancing the QoS of satellite edge computing services. therefore, we propose a computation offloading strategy based on deep reinforcement learning (DRL) for multi-satellite cooperative computing scenarios (DQN-SCCO). First, the optimization problem is formulated as a Markov decision process (MDP), and the optimal solution to the problem is approached through a deep Q-network (DQN). Simulation results show that DQN-SCCO can effectively reduce the task set response delay and improve the task offloading success rate compared to baseline algorithms.
this paper proposes a radar high-resolution range profile (HRRP) recognition algorithm based on ResNet, combined withthe SE (Squeeze-and-Excitation) channel attention mechanism. In most current HRRP target recognitio...
详细信息
Placement and routing, as pivotal aspects of the physical design process in analog integrated circuit(IC) design, have encountered numerous new constraints and challenges amid the recent rapid advancements in analog I...
详细信息
暂无评论