Rice Plant Disease Detection using Convolutional Neural Networks by A. Bala Ayyappan, T. Gobinath, M. Kumar, A. Sivaramakrishnan

“…The CNN model is trained on images of different plant diseases, and various models are evaluated to determine the most effective one for disease identification. …”
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Magnetic Moment Estimation Algorithm Based on Convolutional Neural Network by Xiuzhi You, Junqian Zhang, Bingyang Chen, Ke Zhang, Xiaodong Liu, Bin Yan, Wanhua Zhu

“…This paper proposes a magnetic moment estimation algorithm that combines a scalar magnetic field sensor and the three components of the local geomagnetic field with a convolutional neural network (CNN). The simulation results demonstrate that the proposed algorithm performs well in noise environments with a signal-to-noise ratio (SNR) greater than −5 dB. …”
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CSC-GCN: Contrastive semantic calibration for graph convolution network by Xu Yang, Kun Wei, Cheng Deng

“…The basic idea is the node features obtained from different aggregation operations should be similar. …”
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Convolutive blind source separation method based on tensor decomposition by Baoze MA, Tianqi ZHANG, Zeliang AN, Pan DENG

“…A convolutive blind source separation algorithm was proposed based on tensor decomposition framework, to address the estimation of mixed filter matrix and the permutation alignment of frequency bin simultaneously.Firstly, the tensor models at all frequency bins were constructed according to the estimated autocorrelation matrix of the observed signals.Secondly, the factor matrix corresponding to each frequency bin was calculated by tensor decomposition technique as the estimated mixed filter matrix for that bin.Finally, a global optimal permutation strategy with power ratio as the permutation alignment measure was adopted to eliminate the permutation ambiguity in all the frequency bins.Experimental results demonstrate that the proposed method achieves better separation performance than other existing algorithms when dealing with convolutive mixed speech under different simulation conditions.…”
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Battery Life Evaluation Method Based on Temporal Convolution Network by SUN Yushu, AN Juan, HUANG Cunqiang, ZHANG Shunzhen, DANG Yanyang, PEI Wei, TANG Xisheng

“…Although Pearson correlation and TCN-based analysis yield similar rankings, both focus primarily on the top features. Due to the different principles of these methods, their outcomes often diverge significantly. …”
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Improved Convolutional Neural Networks for Course Teaching Quality Assessment by Yun Liu

“…This effectively distinguishes between seven different expressions in the database. The model proposed in this paper can obtain the changes of students’ facial expressions in class and evaluate students’ learning status, thus promoting the improvement of teaching quality. …”
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Application of convolutional neural networks in the intelligence security system subsystem by V. S. Demeshko, A. I. Фёдоров

“…Training and verification of the recognition quality of architecture data was carried out on an experimentally created data set with a human image on a contrasting background and at different ranges. The results obtained indicate the possibility of using a convolutional neural network in the security system and its ability to work in real time.…”
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Frame points attention convolution for deep learning on point cloud by Luyang Li, Ligang He, Jinjin Gao, Xie Han

“…FPAC then combines the quantified correlations with the weights of the frame points to generate spatially continuous filters. The convolution weights for different local areas in the filters are calculated dynamically, without relying on generative models or probabilistic assumptions. …”
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AN ENHANCED MULTIMODAL BIOMETRIC SYSTEM BASED ON CONVOLUTIONAL NEURAL NETWORK by LAWRENCE OMOTOSHO, IBRAHIM OGUNDOYIN, OLAJIDE ADEBAYO, JOSHUA OYENIYI

“…In multimodal biometrics system, the utilization of different algorithms for feature extraction, fusion at feature level and classification often to complexity and make fused biometrics features larger in dimensions. …”
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Compression of Marine Environmental Data Using Convolutional Attention Autoencoder by Xuehai Sun, Peiyu Wang, Yanxia Zhou, Kedi Wu, Limin Huang, Xuewen Ma

“…This study proposes a convolutional attention autoencoder (CAAE) to compress and reconstruct three-dimensional temperature fields and evaluates its performance across different depths and compression ratios. …”
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Spectral-Spatial Convolutional Hybrid Transformer for Hyperspectral Image Classification by Haixin Sun, Jingwen Xu, Fanlei Meng, Mengdi Cheng, Qiuguang Cao

“…First, the spectral pyramid 3D convolution and 2D convolution are combined to extract joint and detailed spectral-spatial features. …”
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Classification of Some Barley Cultivars with Deep Convolutional Neural Networks by Fatih Bayram, Mustafa Yıldız

“…In this research, a novel image database consisting of 2800 images were created to classify 14 barley cultivars. Six different deep convolutional neural network models were designed based on a transfer learning method with pretrained DenseNet-121, DenseNet-169, DenseNet-201, InceptionResNetV2, MobileNetV2 and Xception networks. …”
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Explainable classification of goat vocalizations using convolutional neural networks. by Stavros Ntalampiras, Gabriele Pesando Gamacchio

“…This paper advances classification of goat vocalizations leveraging a publicly available dataset recorded at diverse farms breeding different species. We developed a Convolutional Neural Network (CNN) architecture tailored for classifying goat vocalizations, yielding an average classification rate of 95.8% in discriminating various goat emotional states. …”
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Identifying Capsule Defect Based on an Improved Convolutional Neural Network by Junlin Zhou, Jiao He, Guoli Li, Yongbin Liu

“…By comparing the results of RACNN with different parameters, a detection method based on the optimal parameters of the RACNN model is finally selected. …”
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Emotion recognition based on convolutional gated recurrent units with attention by Zhu Ye, Yuan Jing, Qinghua Wang, Pengrui Li, Zhihong Liu, Mingjing Yan, Yongqing Zhang, Dongrui Gao

“…Studying brain activity and deciphering the information in electroencephalogram (EEG) signals has become an emerging research field, and substantial advances have been made in the EEG-based classification of emotions. However, using different EEG features and complementarity to discriminate other emotions is still challenging. …”
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Brain tumor classification using deep convolutional neural networks by M. Nurtay, M. Kissina, A. Tau, A. Akhmetov, G. Alina, N. Mutovina

“…The primary aim was to assess the effectiveness of different CNN architectures in accurately identifying brain tumors. …”
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Epileptic Seizure Prediction With Multi-View Convolutional Neural Networks by Chien-Liang Liu, Bin Xiao, Wen-Hoar Hsaio, Vincent S. Tseng

“…This work uses the two domains of EEGs, including frequency domain and time domain, to provide two different views for the same data source. Subsequently, this work proposes a multi-view convolutional neural network framework to predict the occurrence of epilepsy seizures with the goal of acquiring a shared representation of time-domain and frequency-domain features. …”
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An intrusion detection model based on Convolutional Kolmogorov-Arnold Networks by Zhen Wang, Anazida Zainal, Maheyzah Md Siraj, Fuad A. Ghaleb, Xue Hao, Shaoyong Han

“…As well, intrusion detection, the subject of this paper, relies heavily on it. Different intrusion detection models have been constructed using ANNs. …”
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Ocean wave power forecasting using convolutional neural networks by Pedro Bento, José Pombo, Maria do Rosário Calado, Sílvio Mariano

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Self-Denoising of BOTDA Using Deep Convolutional Neural Networks by Di Qi, Chun-Kit Chan, Xun Guan

“…We propose the self-denoising network (SDNet), a self-supervised network based on a convolutional neural network (CNN), for Brillouin trace denoising. …”
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