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We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks. We show that a simple CNN with little hyperparameter tunin...

This paper explores the application of convolutional neural networks (CNNs) in predictive modelling for seismic events and flood risks, with a particular focus on forecasting extreme quantile events that exceed historica...

The management and operation of the power system would be significantly enhanced if accurate prior knowledge of power exchanges were provided, which could provide valuable insights into the system and help predict the re...

Abstract Marine habitat maps are essential tools for marine spatial planning, providing information for decision‐making in conservation and resource management. Accurate classification of benthic habitats supports thei...

Abstract Snowfall is the primary contributor to Antarctic surface mass balance. Identifying regional‐scale mechanisms that drive heavy snowfall provides context for changes in Antarctic surface mass balance in a warmer...

IntroductionReliable classification of lung nodules from computed tomography (CT) images remains a challenging problem due to variations in image intensity, noise, and unstable feature representations during deep network...

BackgroundRecently, plant disease detection and classification have become major concerns in agriculture. Early detection of plant diseases supports farmers to take precautionary actions to prevent the spread of infectio...

Background For those with hearing loss, sign language (SL) is an essential communication tool. The most common and basic type of SL is American SL (ASL). ASL plays a vital role in various communicative contexts, includin...

Recent advances in computer vision and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly increased road safety. CNNs were used in this work to automatically detect and categorise traffi...

Wildfires pose a grave danger and threat to both human health and the environment, which is why early detection of wildfires is crucial. In this study, a convolutional neural network, which is a deep learning technique f...

In recent years, convolutional neural networks and deep neural networks have been used extensively in various fields of analytical chemistry. The use of these models for calibration tasks has been highly effective; howev...

In this research, we address a critical problem for strawberry growers in Lima: the management of phytosanitary diseases. Traditionally, these farmers relied on time-consuming, imprecise, and error-prone visual observati...

IntroductionEarly and accurate diagnosis of skin cancer has a huge impact on the survival rate of patients and deep learning-based CNN and dermatologists' intelligence support can fasten the diagnosis not only within the...

Abstract Advances in artificial intelligence (AI) and multi-omics integration are reshaping precision oncology by enabling deeper mechanistic understanding, improved characterization of tumor heterogeneity, and the accel...

Stellar population measurements in integral field unit surveys are often limited by low signal-to-noise ratios (S/Ns) in low-surface-brightness spaxels. Using controlled synthetic experiments, we investigate whether a de...

Abstract Underwater imaging suffers from various challenges such as color distortion, low contrast, and reduced visibility caused by light attenuation. Addressing these issues is crucial for improving the performance of ...

With the rapid advancement of online education, students’ sentiment feedback serves as a pivotal factor in enhancing course quality and refining pedagogical strategies. However, conventional sentiment analysis approach...

In the current digital era, image classification of fruits, particularly apples, has become crucial for various applications, ranging from agriculture to retail. This research focuses on the utilization of Convolutional ...

Abstract The current work on emotion recognition considering EEG signals has attracted significant attention due to its advantages in fields like mental health, neural computing, and human-computer interaction. Nonethele...

Abstract The co-frequency vibration fault is one of the common faults in the operation of rotating equipment, and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitor...

Media sosial sebagai media informasi dan komunikasi mulai berkembang pesat sejak internet mudah diakses. Orang dengan mudah menyatakan pendapat, ekspresi, opini, dan informasi melalui tulisan pada media sosial. Opini ata...

We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On the test data, we achieved top-1 and top-5 e...

We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e.g., 10-150 MFLOPs). The new architecture utilizes two...

The Babad Lombok is an ancient literary or manuscripts document that generally contains stories about the origins of the people of Lombok. This document is written on a lontar leaf, which in the past was used to write ma...