Learning Face Pareidolia via Global Feature Transfer by Usfita Kiftiyani, Seungkyu Lee

“…Convolutional Neural Networks learn different details of features across various layers, progressively extracting features from low-level aspects such as edges to high-level semantic concepts. …”
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Lightweight image super-resolution network based on muti-domain information enhancement by KOU Qiqi, LIU Gui, JIANG He, CHEN Liangliang, CHENG Deqiang

“…Aiming to solve the problems that the reconstruction capability of single-domain features was limited and deep convolutional neural networks used in existing single-image super-resolution reconstruction tasks were difficult to deploy on mobile terminals due to the large number of parameters and high computational requirements, a lightweight image super-resolution network based on multi-domain information enhancement was proposed. …”
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Advancements of Deep Learning Model-Based Rehabilitation Training System by Xu Chiyu

“…In this paper, one of the studies proposed the concept of posture-guided matching based on paired Siamese Convolutional Neural Networks (SCNN), abbreviated as ST-AMCNN, on a dataset of the traditional Chinese rehabilitation training Baduanjin. …”
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Explainable Offline‐Online Training of Neural Networks for Parameterizations: A 1D Gravity Wave‐QBO Testbed in the Small‐Data Regime by Hamid A. Pahlavan, Pedram Hassanzadeh, M. Joan Alexander

“…Abstract There are different strategies for training neural networks (NNs) as subgrid‐scale parameterizations. …”
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Towards Understanding the Analysis, Models, and Future Directions of Sports Social Networks by Zhongbo Bai, Xiaomei Bai

“…Thirdly, we present and compare different sports social network models that have been used for sports social network analysis, modeling, and prediction. …”
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Generate vector graphics of fine-grained pattern based on the Xception edge detection. by Anqi Chen, Yicui Peng, Meng Li, Hao Chen, Chang Liu, Jinrong Hu, Xiang Wen, Guo Huang

“…Then, the Xception algorithm based on convolutional neural networks(CNNs) is used for edge detection and extraction to generate vector graphics of the patterns. …”
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Generative Adversarial Network for Damage Identification in Civil Structures by Zahra Rastin, Gholamreza Ghodrati Amiri, Ehsan Darvishan

“…Most of the proposed methods employ supervised algorithms that require data from different damaged states of a structure in order to monitor its health conditions. …”
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Assessment of Driver Stress using Multimodal wereable Signals and Self-Attention Networks by Pavan Kaveti, Ganapathy Nagarajan

“…In this study, we address this challenge by exploring a 1D convolutional neural network (CNN) with self-attention mechanisms on multimodal data. …”
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Hybrid-RViT: Hybridizing ResNet-50 and Vision Transformer for Enhanced Alzheimer's disease detection. by Hongjie Yan, Vivens Mubonanyikuzo, Temitope Emmanuel Komolafe, Liang Zhou, Tao Wu, Nizhuan Wang

“…The proposed Hybrid-RViT model integrates the pre-trained convolutional neural network (ResNet-50) with the Vision Transformer (ViT) to classify brain MRI images across different stages of AD. …”
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AI-Driven Solutions for Early Detection of Plant Diseases by Saha Laboni, Lalmawipuii R.

“…A CNN model is developed and trained in this research on a large annotated dataset of high-resolution plant images from different agricultural environments of healthy and diseased plants. …”
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Deep Learning Based DDoS Attack Detection by Xu Ziyi

“…The classification resulting from this model yielded high accuracy with robust results for different attack scenarios. Results reflect the potential superiority of the given model in detecting DDoS attacks. …”
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Text classification model of rare earths patents based on ERNE-CAB-CNN by Liao Liefa, Shi Lijiao

“…Combined with ERNIE and Convolutional Neural Network (CNN), an innovative model ERNE-CAB-CNN for rare earth patent text classification is constructed. …”
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A Deep Learning Approach Toward Analyzing the Cross-Lingual Acoustic-Phonetic Similarities in Multilingual Speech Emotion Recognition by Syeda Tamanna Alam Monisha, Sadia Sultana

“…This study uses deep learning to explore the influence of phonetic similarities across languages on multilingual SER systems in diverse linguistic contexts. A deep convolutional neural network (DCNN) model was employed to evaluate the performance of speech emotion detection in a multilingual context. …”
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Universal slip detection of robotic hand with tactile sensing by Chuangri Zhao, Yang Yu, Zeqi Ye, Ziyang Tian, Yifan Zhang, Ling-Li Zeng

“…Second, according to the principle of deep double descent, we designed a lightweight universal slip detection convolutional network for different grasp types (USDConvNet-DG) to classify grasp states (no-touch, slipping, and stable grasp). …”
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TGF-Net: Transformer and gist CNN fusion network for multi-modal remote sensing image classification. by Huiqing Wang, Huajun Wang, Linfen Wu

“…Meanwhile, the transformer-based spectral feature extraction module (TSFEM) was designed by combining the different characteristics of remote sensing images and considering the problem of orderliness of the sequence between hyperspectral image (HSI) channels. …”
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Cross-attention swin-transformer for detailed segmentation of ancient architectural color patterns by Lv Yongyin, Yu Caixia

“…The results highlight the model's ability to generalize well across different tasks and provide robust segmentation, even in challenging scenarios. …”
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ReLU, Sparseness, and the Encoding of Optic Flow in Neural Networks by Oliver W. Layton, Siyuan Peng, Scott T. Steinmetz

“…The present study investigates the influence of different activation functions—ReLU, leaky ReLU, GELU, and Mish—on the accuracy, robustness, and encoding properties of convolutional neural networks (CNNs) and multi-layer perceptrons (MLPs) trained to estimate self-motion from optic flow. …”
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Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

“…It has a series of operations, including depth-separable convolution, as well as SE modules and the Hard-swish activation function. …”
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ETUDE DE LA REFLEXION DE L’ONDE ULTRASONORE DANS LE DOMAINE TEMPOREL by Kahina LOUANI

“…En application, on a choisi différents signaux d’entrée puis, par convolution numérique, on retrouve la forme du signal correspondant à l’onde réfléchie. …”
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Using deep learning for detecting BotCloud by Guang KOU, Guang-ming TANG, Shuo WANG, Hai-tao SONG, Yuan BIAN

“…The differences of the basic network flow characteristics between BotCloud and normal cloud services were not obvious, and this led to the inefficiency of the method in BotCloud detection based on network flow characteristics analysis. …”
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