Automatic political discourse analysis with multi-scale convolutional neural networks and contextual data by Aritz Bilbao-Jayo, Aitor Almeida

“…To do so, the authors have built a discourse classifier using multi-scale convolutional neural networks in seven different languages: Spanish, Finnish, Danish, English, German, French, and Italian. …”
Get full text

The convolution-induced topology on L∞(G) and linearly dependent translates in L1(G) by G. Crombez, W. Govaerts

“…From this, we deduce that τc is different from the w∗-topology on L∞(G) whenever G is infinite. …”
Get full text

Target detection of helicopter electric power inspection based on the feature embedding convolution model. by Dakun Liu, Wei Zhou, Linzhen Zhou, Wen Guan

“…This study aims to improve the helicopter electric power inspection process by using the feature embedding convolution (FEC) model to solve the problems of small scope and poor real-time inspection. …”
Get full text

Convolutional Interval-Valued Neutrosophic Network for Intelligent Evaluation of Smart Clothing Design Choices by Fengfang Wu

“…The Neutrosophic representation enables modeling uncertainty, inconsistency, and hesitancy in decision-making by assigning interval-ed membership degrees for different views of smart clothes design. Using the interval-valued representations, we enable robust learning and interpretation of user partialities while handling vague feedback. …”
Get full text

Integration of unpaired single cell omics data by deep transfer graph convolutional network. by Yulong Kan, Yunjing Qi, Zhongxiao Zhang, Xikeng Liang, Weihao Wang, Shuilin Jin

“…Thus, scTGCN shows high label transfer accuracy and effectively knowledge transfer across different modalities.…”
Get full text

SL-GCNN: A Graph Convolutional Neural Network for Granular Human Motion Recognition by Yang Li, Jingyu Zhang

“…By leveraging contrastive learning, the model refines hidden layer features and isolates output layer features, effectively addressing the challenges posed by subtle differences in granular motions. Experimental results on the two different datasets demonstrate that SL-GCNN outperforms existing state-of-the-art methods, achieving accuracies of 92.73% and 97.47% on the X-Sub and X-View benchmarks of NTU_RGB_plus_D, and 89.19% and 90.56% on the X-Sub and X-View benchmarks of NTU_RGB_plus_D_120, respectively. …”
Get full text

TEA-GCN: Transformer-Enhanced Adaptive Graph Convolutional Network for Traffic Flow Forecasting by Xiaxia He, Wenhui Zhang, Xiaoyu Li, Xiaodan Zhang

“…Specifically, we design an adaptive graph convolutional module to dynamically capture implicit road dependencies at different time levels and a local-global temporal attention module to simultaneously capture long-term and short-term temporal dependencies. …”
Get full text

Perbandingan Random Forest dan Convolutional Neural Network dalam Memprediksi Peralihan Pelanggan by Dewa Adji Kusuma, Atika Ratna Dewi, Andreas Rony Wijaya

“…The limitation of this research is how to handle the two algorithms being compared. Both use different approaches, namely Supervised Learning and Deep Learning. …”
Get full text

MagNet: Automated Magnetic Mineral Grain Morphometry Using Convolutional Neural Network by Zhaowen Pei, Liao Chang, Pengfei Xue, Richard J. Harrison

“…MagNet is open‐source and can easily be extended to process different types of mineral images. This tool has the potential, therefore, to extract key quantitative information of magnetic mineral populations within heterogeneous terrestrial and meteoritic samples for the interpretations of Earth and planetary processes.…”
Get full text

Bearing Life Prediction Method Based on Parallel Multichannel Recurrent Convolutional Neural Network by Jianmin Zhou, Sen Gao, Jiahui Li, Wenhao Xiong

“…The back of the model is the recurrent convolution layer to model the temporal dependence relationship under different degradation features. …”
Get full text

EFFICIENCY AND ACCURACY OF CONVOLUTIONAL AND FOURIER TRANSFORM LAYERS IN NEURAL NETWORKS FOR MEDICAL IMAGE CLASSIFICATION by Fauzi Nafi'udin, Hasih Pratiwi, Etik Zukhronah

“…However, the convolution layer has an advantage in terms of model size, although it is not significantly different from the Fourier transform layer. …”
Get full text

Recommending third-party APIs via using lightweight graph convolutional neural networks by Meijiao Zhang, Xianhao Pan, Jiajin Mai, Mingdong Tang, Tien-Hsiung Weng

“…It first learns the embedding of users and APIs from the user-API interaction graph, and then adopts a weighted summation operator to aggregate the embeddings learned from different propagation layers for API recommendation. …”
Get full text

Removing Stripe Noise From Infrared Cloud Images via Deep Convolutional Networks by Pengfei Xiao, Yecai Guo, Peixian Zhuang

“…To further improve the performance, we propose a local-global combination structure model, which combines the representations of different layers for recovering the rich details of infrared cloud images. …”
Get full text

A Novel Approach for Tomato Leaf Disease Classification with Deep Convolutional Neural Networks by Gizem Irmak, Ahmet Saygılı

“…In contrast, a novel convolutional neural network (CNN) framework, complete with unique parameters and layers, was utilized for deep learning. …”
Get full text

Facial Expression Recognition using Convolutional Neural Networks with Transfer Learning Resnet-50 by Annisa Ayu Istiqomah, Christy Atika Sari, Ajib Susanto, Eko Hari Rachmawanto

Get full text

Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network by Aythem Khairi Kareem, Mohammed M. AL-Ani, Ahmed Adil Nafea

Get full text

Local kernel renormalization as a mechanism for feature learning in overparametrized convolutional neural networks by R. Aiudi, R. Pacelli, P. Baglioni, A. Vezzani, R. Burioni, P. Rotondo

“…In this work, we present a theoretical framework that provides a rationale for these differences in one-hidden-layer networks; we derive an effective action in the so-called proportional limit for an architecture with one convolutional hidden layer and compare it with the result available for fully-connected networks. …”
Get full text

Training Sample Formation for Convolution Neural Networks to Person Re-Identification from Video by S. A. Ihnatsyeva, R. P. Bohush

“…Another PolReID1077 advantage is the video data use obtained from external and internal surveillance in a large number of different filming locations. Therefore, the people images in the created set are characterized by the variability of the background, brightness and color characteristics. …”
Get full text

Diagnosis of Alzheimer Disease Using 2D MRI Slices by Convolutional Neural Network by Fanar E. K. Al-Khuzaie, Oguz Bayat, Adil D. Duru

“…There are many kinds of brain abnormalities that cause changes in different parts of the brain. Alzheimer’s disease is a chronic condition that degenerates the cells of the brain leading to memory asthenia. …”
Get full text

CLASS IMBALANCE PROBLEM IN ANTI-FRAUD PROBLEM: METRICS, SAMPLING AND CONVOLUTIONAL NEURAL NETWORKS by Ruslan Ch. Bobonazarov

“…Researchers, using publicly available datasets, apply different approaches to model evaluation, some of which are not effective in conditions of severe class imbalance. …”
Get full text