Dynamic convolution models for cross-frontend keyword spotting by Rongqi Liu, Wenkang Chen, Xuejun Zhang

“…The dynamic convolution model enables the adaptive capture of diverse and time-varying acoustic patterns, while the mutual learning strategy effectively leverages complementary features extracted from multiple audio frontends to enhance the model’s generalization across different input conditions. …”
Get full text

Convolutional neural network for dog breed recognition system by К. Хотінь, В. Шимкович, П. Кравець, А. Новацький, Л. Шимкович

“… The object of research is models of convolutional neural networks and datasets for training convolutional neural networks. …”
Get full text

Automatic Image Colorization Based on Convolutional Neural Networks by L. V. Serebryanaya, V. V. Potaraev

“…Software tool was created which allows to perform learning of different neural networks and colorization of graphical information. …”
Get full text

Convolutional Neural Networks for Predicting Power Outages in Baghdad by Saja Jafar Jawad, Shaymaa. W. Al-Shammari

“…This paper introduces a real-world time series dataset for Baghdad city, including historical outages, weather conditions (such as temperature), and power overloads, and analyzes the correlation among these parameters in different seasons. The research uses this dataset to train one-dimensional Convolutional Neural Networks (1D CNN) to find patterns and relationships that can accurately predict when power outages can happen in the long term and short term to improve the management of the Baghdad electricity grid through data-driven networks. …”
Get full text

Augmented Graph Convolutional Network for Enhancing Label Reachability by Xiangyi Wang, Fengjun Zhang, Wei Teng, Baoda Liu

“…Graph Convolutional Networks (GCNs) have emerged as a leading approach for semi-supervised node classification. …”
Get full text

Flood Image Classification using Convolutional Neural Networks by Olusogo Julius Adetunji, Ibrahim Adepoju Adeyanju, Adebimpe Omolayo Esan, Adedayo Aladejobi Sobowale Sobowale

“…Between the years 2002- 2023, flood has caused death of over 200,000 people globally and occurred majorly in resource poor countries and communities. Different machine learning approaches have been developed for the prediction of floods. …”
Get full text

An Ensemble of Convolutional Neural Networks for Sound Event Detection by Abdinabi Mukhamadiyev, Ilyos Khujayarov, Dilorom Nabieva, Jinsoo Cho

“…Our dataset contains 5055 audio files of different lengths totaling 14.14 h and strongly labeled data. …”
Get full text

Cucumber Leaf Segmentation Based on Bilayer Convolutional Network by Tingting Qian, Yangxin Liu, Shenglian Lu, Linyi Li, Xiuguo Zheng, Qingqing Ju, Yiyang Li, Chun Xie, Guo Li

“…For cucumber leaves at different growth stages and under various lighting conditions, the Precision, Recall and Average Precision (<i>AP</i>) metrics for object recognition are 97%, 94% and 96.57%, respectively. …”
Get full text

Proposal of a Methodology Based on Using a Wavelet Transform as a Convolution Operation in a Convolutional Neural Network for Feature Extraction Purposes by Nora Isabel Pérez-Quezadas, Héctor Benítez-Pérez, Adrián Durán-Chavesti

“…Using methodological tools to construct feature extraction from multidimensional data is challenging. Different treatments are required to build a coherent representation with those features that can be attenuated by various phenomena inherent to the observed process. …”
Get full text

From Social to Academic: Associations and Predictions Between Different Types of Peer Relationships and Academic Performance Among College Students by Jiadong Tian, Jiali Lin, Dagang Li

“…This study aims to expose the correlation between different types of social behaviors and the academic performance of college students, and then to predict the academic performance of college students based on their social characteristics. …”
Get full text

The effect of different doses levels of silver nanoparticles (AgNPs) on the kidney and liver in Albino male Rat. Histopathological study by Baghdad Science Journal

Get full text

A GNSS-IR Soil Moisture Inversion Method Considering Multi-Factor Influences Under Different Vegetation Covers by Yadong Yao, Jixuan Yan, Guang Li, Weiwei Ma, Xiangdong Yao, Miao Song, Qiang Li, Jie Li

“…Additionally, the analysis of different surface types showed that the method achieved higher accuracy in grassland and open shrubland areas, with all models reaching R² values above 0.9. …”
Get full text

Prediction of Winter Wheat Yield and Interpretable Accuracy Under Different Water and Nitrogen Treatments Based on CNNResNet-50 by Donglin Wang, Yuhan Cheng, Longfei Shi, Huiqing Yin, Guangguang Yang, Shaobo Liu, Qinge Dong, Jiankun Ge

Get full text

Simulated Centrifugal Fan Blade Fault Diagnosis Based on Modulational Depthwise Convolution–One-Dimensional Convolution Neural Network (MDC-1DCNN) Model by Zhaohui Ren, Yulin Liu, Tianzhuang Yu, Shihua Zhou, Yongchao Zhang, Zeyu Jiang

“…Second, multiple DWconv layers of different sizes are introduced to capture high-frequency shocks and low-frequency fluctuation information of different frequencies and durations in the signal. …”
Get full text

Importance Analysis of Vegetation Change Factors in East Africa Based on Machine Learning by Zhang Xiumei, Ma Bo, Zhang Yijie

“…[Objective] A factor importance analysis of vegetation changes in East Africa based on different machine learning algorithms was conducted to measure the accuracy and applicability of the different algorithms in order to provide a scientific basis for protecting, restoring, and promoting sustainable forest management and comprehensive prevention and control of soil erosion. …”
Get full text

Accelerating Brain MR Imaging With Multisequence and Convolutional Neural Networks by Zhanhao Mo, He Sui, Zhongwen Lv, Xiaoqian Huang, Guobin Li, Dinggang Shen, Lin Liu, Shu Liao

Get full text

CNN Convolutional layer optimisation based on quantum evolutionary algorithm by Tzyy-Chyang Lu

“…In the simulation part, CIFAR-10 (including 50k training images and 10k test images in 10 classes) is used to train VGG-19 and 20-layer, 32-layer, 44-layer and 56-layer CNN networks, and compare the difference between the optimal and non-optimal convolutional layer networks. …”
Get full text

Activation function cyclically switchable convolutional neural network model by İsmail Akgül

“…This study presents a different approach apart from fixed or trainable AF approaches. …”
Get full text

Improving deep convolutional neural networks with mixed maxout units by Hui-zhen ZHAO, Fu-xian LIU, Long-yue LI, Chang LUO

“…The maxout units have the problem of not delivering non-max features， resulting in the insufficient of pooling operation over a subspace that is composed of several linear feature mappings,when they are applied in deep convolutional neural networks.The mixed maxout (mixout) units were proposed to deal with this constrain.Firstly,the exponential probability of the feature mappings getting from different linear transformations was computed.Then,the averaging of a subspace of different feature mappings by the exponential probability was computed.Finally,the output was randomly sampled from the max feature and the mean value by the Bernoulli distribution,leading to the better utilizing of model averaging ability of dropout.The simple models and network in network models was built to evaluate the performance of mixout units.The results show that mixout units based models have better performance.…”
Get full text

Unsupervised intrusion detection model based on temporal convolutional network by LIAO Jinju, DING Jiawei, FENG Guanghui

“…In addition, UDMT can adopt different privacy layer modes, and the configuration was flexible to meet the requirements of different detection rates and detection delays. …”
Get full text