Titlebook: Recent Challenges in Intelligent Information and Database Systems; 16th Asian Conferenc Ngoc Thanh Nguyen,Richard Chbeir,Krystian Wojtkiew

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SnapQuake: Damage Detection in?Snapchat Videos for?Earthquake Assessmentncing humanitarian event detection and assessment during catastrophes, notably the 2023 Syria earthquake, employing an innovative crisis event detection method with Snapchat. A refined listening model captured relevant Snapchats during targeted events, forming a dataset of 300 videos. Training the m

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Lecture Video Summarization Using Deep Learninghile these lectures effectively teach topics from scratch, they pose challenges for quick revisions. Viewers struggle to control the pace, often interrupting playback to navigate the content. Additionally, finding specific information within the video and skimming the unstructured transcript for rel

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Philippine Lime (Calamansi) Disease Detection and?Classification Using YOLOv8 Model experienced a production decline of 1.5% to 12.903 thousand metric tons in early 2022, with the prevalence of calamansi diseases as one of the main factors. Calamansi farmers often neglect manual inspection due to its tedious nature, prompting the need for a more advanced approach. To address this,

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Graphics and?Vision’s Camera Calibration and?Applications to?Neural Radiance Fieldsorks enable Neural Radiance Fields (NERF) ready for using with those two tasks. In combination with training and tuning, techniques for enriching data, for example, data augmentation and masking, are also crucial for making deep-learning successfully. Inspired by the field of computer vision (e.g.,

COMA

LSTM Based Time Series Forecasting of Noisy Signals prediction model is used to generate, reproduce and forecast the values of the time series data without the practical experimental set up where the information can be useful for various applications. In this paper, Long Short Term Memory (LSTM) neural network based time series prediction for noisy

dissolution

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Bag of?Activities for?Customer Churn Prediction in?e-Book Subscription Domainme a very important and challenging issue. This is due to the fact that many reports convict that it is much more expensive to acquire new customers than to retain current ones. This paper focuses on developing a set of the most relevant characteristics in the subscription industry that significantl

Aids209

Forecasting WTI & Brent Crude Oil Price Using LSTM, Prophet and XGBoost – Comparative Analysis factors such as political events, weather factors, but also wars and so-called demand and supply shocks. The activities of the OPEC organization are also important. In commodity trade, there are two main types of crude oil, the so-called WTI and Brent. It seems that there is a lack of direct compar