Titlebook: Deep Learning and Visual Artificial Intelligence; Proceedings of ICDLA Vishal Goar,Aditi Sharma,M. Firoz Mridha Conference proceedings 2024

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Deep Learning in Health Care: A Systematic Analytical Review,own to be most smart technology in healthcare system that specifies the intensifying density. In order to extract unseen patterns and corresponding important information from high quantity of data, which traditional analysis are unable to do in realistic length of time, ML methods are utilized. Deep

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Eye-Activated Scroll Control: Enhancing User Experience,virtual environments. With the help of computer vision, facial landmarks recognition as well as eye-tracking algorithm, individuals can adjust the scrolling of documents with their eyes movement. The system views the individual‘s intent by taking the individual‘s face as input and also specifically

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,A Critical Analysis Using Data Mining Techniques to Predict Students’ Educational Performance: Analintellectual parameters play a crucial role in predicting students’ educational performance. While intellectual parameters such as cognitive abilities and academic aptitude have traditionally been considered the primary determinants of academic success, research has increasingly recognized the influ

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A Comprehensive Comparative Analysis of Artificial Intelligence-Based Recommender System Algorithmsxamining their use in improving the travel search process. In the rapidly evolving digital world, personalized suggestions are crucial since they greatly increase user satisfaction and engagement. This paper examines the concept of trip recommendation systems and evaluates various established algori

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Flood-Prone Road Recognition: Enhancing Resilience Through Identification Analysis,anagement. This research presents an approach for flood-prone road detection leveraging a hybrid approach of combining convolutional neural network (CNN) and long short-term memory (LSTM) architectures. The proposed model harnesses the feature extraction abilities of CNNs and the sequential learning

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Deep Learning in Electronic Word-of-Mouth: A Comprehensive Review and Future Directions,evolution of eWOM, the challenges associated with its analysis, and the role of deep learning in addressing these challenges. Additionally, we discuss key applications, methodologies, and current advancements in the field, along with potential future directions for research and development.