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Keyword: MultimodalIdentifying Comprehension Faults Through Word Embedding and Multimodal Analysis
This study establishes a method for determining whether learners have an understanding of data science. Data science requires knowledge in various fields, which makes many learners give up. To prevent learners from being discouraged, it is necessary to judge the comprehension of the principles in each specified skill. It is important to assess not only…
Read More3D Facial Feature Tracking with Multimodal Depth Fusion
As models based in artificial intelligence increase in sophistication, there is a higher demand for the integration of hardware components to heighten real-world implementations. Both facial feature tracking and shape-from-focus are known techniques in computer vision. However, the combination of these two elements, particularly in a cost-effective configuration, has not been extensively explored. In this…
Read MoreA Circular Invariant Convolution Model-Based Mapping for Multimodal Change Detection
The large and ever-increasing variety of remote sensing sensors used in satellite imagery today explains why detecting changes between identical locations in images that are captured, at two separate times, from heterogeneous capturing systems is a major and challenging recent research problem in the field of satellite imaging for fast and accurate determination of temporal…
Read MoreQ-Learning versus SVM Study for Green Context-Aware Multimodal ITS Stations
Intelligent Transportation Systems (ITS) applications can take big advantage of Context Awareness approaches. Parameters such as user mobility, passengers comfort reaction and pollution emission levels (CO2) can enrich such applications during the decision making phase. Moreover, the expanding in ITS services offers great opportunities for travelers to find the best route to reach their destinations…
Read MoreGenerative Artificial Intelligence and Prompt Engineering: A Comprehensive Guide to Models, Methods, and Best Practices
This article enhances discussions on Generative Artificial Intelligence (GenAI) and prompt engineering by exploring critical pitfalls and industry-specific advantages. It begins with a foundational overview of AI evolution, emphasizing how generative models such as GANs, VAEs, and Transformers have revolutionized language processing, image generation, and drug discovery. Prompt engineering is highlighted as a key methodology…
Read MoreBiometric System Vulnerabilities: A Typology of Metadata
This study presents a root cause analysis of biometric vulnerabilities and provides a comprehensive typology of metadata in biometric adaptation. Although they are more reliable and secure than traditional authentication methods, biometric techniques are subject to vulnerabilities that pose challenges. Faced with the proliferation of cases of identity theft and fraud, biometrics is increasingly used…
Read MoreMRI images Enhancement and Brain Tumor Segmentation
Brain tumor is the abnormal growth of cancerous cells in Brain. The development of automated methods for segmenting brain tumors remains one of the most difficult tasks in medical data processing. Accurate segmentation can improve diagnosis, such as evaluating tumor volume. However, manual segmentation in magnetic resonance data is a laborious task. The main problem…
Read MoreHow Effective is Using Lip Movement for Japanese Utterance Training
Lip movements have long been the subject of research. There are many methods of lip movement recognition, such as the calculation of the amount of movement compared to a matching face pattern. In a previous study, we investigated utterance recognition based on the power spectrum by focusing on lip movements, which is one aspect of…
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