A wireless sensor data-based coal mine gas monitoring algorithm with least squares support vector machines optimized by swarm intelligence techniques by Peng Chen, Yonghong Xie, Pei Jin, Dezheng Zhang

“…Using the popular deep neural networks, convolutional neural network and long short-term memory model, as comparisons, a number of experiments are carried out on several UCI machine learning datasets with different features. …”
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RGB imaging-based detection of rice leaf blast spot and resistance evaluation at the canopy scale by XIE Pengyao, FU Haowei, TANG Zheng, MA Zhihong, CEN Haiyan

“…Therefore, this study aims to identify and detect rice leaf blast spots based on RGB imaging of rice canopy combined with mask regions with convolutional neural network (Mask-RCNN), and develop multiple classification models to quantify the number of disease spots and evaluate the association between the number of disease spots and the resistance level by analyzing the quantitative information of different categories of disease spots in RGB images of rice. …”
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3D animation design image detail enhancement based on intelligent fuzzy algorithm by Pu Haitao, Pu Yuang

“…When processing high texture 3D animations, the method cannot effectively optimize for different areas, significantly affecting image quality and detail representation. …”
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A Dynamic Spatio-Temporal Deep Learning Model for Lane-Level Traffic Prediction by Bao Li, Quan Yang, Jianjiang Chen, Dongjin Yu, Dongjing Wang, Feng Wan

“…Specifically, we take advantage of the graph convolutional network (GCN) with a data-driven adjacent matrix for spatial feature modeling and treat different lanes of the same road segment as different nodes. …”
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Chess Position Evaluation Using Radial Basis Function Neural Networks by Dimitrios Kagkas, Despina Karamichailidou, Alex Alexandridis

“…The proposed approach introduces models based on the radial basis function (RBF) neural network architecture trained with the fuzzy means algorithm, in conjunction with a novel set of input features; different methods of network training are also examined and compared, involving the multilayer perceptron (MLP) and convolutional neural network (CNN) architectures and a different set of input features. …”
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Assessing the performance of domain-specific models for plant leaf disease classification: a comprehensive benchmark of transfer-learning on open datasets by David J. Richter, Kyungbaek Kim

“…There exist many different highly-capable models at this time. There also exists a range of plant leaf disease classification image datasets containing different plants and diseases. …”
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Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning by Jie Huang, Yanli Zhao, Zhanxiao Tian, Wei Qu, Xia Du, Jie Zhang, Meng Zhang, Yunlong Tan, Zhiren Wang, Shuping Tan

“…Current diagnostic criteria rely primarily on clinical symptoms, which may not fully capture individual differences and the heterogeneity of the disorder. In this study, a discriminative model of schizophrenic speech based on deep learning is developed, which combines different emotional stimuli and features. …”
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ResnetCPS for Power Equipment and Defect Detection by Xingyu Yan, Lixin Jia, Xiao Liao, Wei Cui, Shuangsi Xue, Dapeng Yan, Hui Cao

“…The core idea is that the network output should remain consistent for the same object at different scales. The proposed framework facilitates weight sharing across different layers within the convolutional network, establishing connections between pertinent channels across layers and leveraging the scale invariance inherent in image datasets. …”
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The analysis of motion recognition model for badminton player movements using machine learning by Xuanmin Zhu, Lizhi Liu, Jingshuo Huang, Genyan Chen, Xi Ling, Yanshuo Chen

“…A badminton stroke recognition method based on Quantum Convolutional Neural Network (QCNN) is proposed. It is then compared with traditional Support Vector Machines (SVM) and Convolutional Neural Network (CNN). …”
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Fast segmentation and multiplexing imaging of organelles in live cells by Karl Zhanghao, Meiqi Li, Xingye Chen, Wenhui Liu, Tianling Li, Yiming Wang, Fei Su, Zihan Wu, Chunyan Shan, Jiamin Wu, Yan Zhang, Jingyan Fu, Peng Xi, Dayong Jin

“…We further show that transfer learning can predict both 3D and 2D datasets from different microscopes, different cell types, and even complex systems of living tissues. …”
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A Method of Trackside Kilometer Post Identification Combined with YOLOv3 Model by QIU Xinhua, WANG Wenkun, JI Yuwen, LI Jia

“…Therefore, an image recognition method based on YOLOv3 was proposed, which could still ensure good recognition accuracy in the face of different illumination, complex background and different forms of image. …”
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Multi-camera video collaborative analysis method based on edge computing by Zhibo QI, Lei DU, Ru HUO, Fan YANG, Tao HUANG

“…In order to reduce the processing volume of multi-camera real-time video data in smart city scenarios, a video collaborative analysis method based on machine learning algorithms at the edge was proposed.Firstly, for the important objects detected by each camera, different key windows were designed to filter the region of interest (RoI) in the video, reduce the video data volume and extract its features.Then, based on the extracted data features, the same objects in the videos from different cameras were annotated, and a strategy for calculating the association degree value between cameras was designed for further reducing the video data volume.Finally, the GC-ReID algorithm based on graph convolutional network (GCN) and re-identification (ReID) was proposed, aiming at achieving the collaborative analysis of multi-camera videos.The experimental results show that proposed method can effectively reduce the system latency and improve the video compression rate while ensuring the high accuracy, compared with the existing video analysis methods.…”
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An FPGA-Based Hardware Accelerator for CNNs Using On-Chip Memories Only: Design and Benchmarking with Intel Movidius Neural Compute Stick by Gianmarco Dinelli, Gabriele Meoni, Emilio Rapuano, Gionata Benelli, Luca Fanucci

“…During the last years, convolutional neural networks have been used for different applications, thanks to their potentiality to carry out tasks by using a reduced number of parameters when compared with other deep learning approaches. …”
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Ultra-Short-Term Power Forecasting Method for Wind-Solar-Hydro Integration Based on Improved GRU-CNN by Xiaogang WU, Jie YAN, Chang GE, Yajie TANG, Chouwei NI, Qingfeng JI

“…The models of wind, solar, and hydro energy systems are very different, and there are multiple uncertainties among them. …”
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An efficient method for predicting temperature field of PC beams with CSWs using thermocouple numerical analysis and random forest algorithm by Haiping Zhang, Hao Long, Fanghuai Chen, Yuan Luo, Xinhui Xiao, Yang Deng, Naiwei Lu, Yang Liu

“…The significant difference in specific heat between concrete and steel results in non-uniform temperature fields in existing PC beam bridges with corrugated steel webs (CSWs) under combined environmental temperature, solar radiation, wind, and thermal radiation. …”
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SambaMixer: State of Health Prediction of Li-Ion Batteries Using Mamba State Space Models by Jose Ignacio Olalde-Verano, Sascha Kirch, Clara Perez-Molina, Sergio Martin

“…Approaches leveraging deep learning architectures have been proposed to predict the SOH using convolutional networks, recurrent networks, and transformers. …”
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Fisheye omnidirectional stereo depth estimation assisted with edge-awareness by Junren Sun, Hao Xue, Shibo Guo, Xunqi Zheng

“…A cost volume is built for different depth hypotheses, which is then regularized using a 3D convolutional network. …”
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Multiscale Feature Filtering Network for Image Recognition System in Unmanned Aerial Vehicle by Xianghua Ma, Zhenkun Yang, Shining Chen

“…These branches employ multiple atrous convolutions at different scales, respectively, and further adaptively generate channel-wise feature responses by emphasizing channel-wise dependencies. …”
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Automatic recognition and representation of text in the form of audio stream by L. V. Serebryanaya, I. E. Lasy

“…It consists of three components: a convolutional encoder, a convolutional decoder, and a transformer. …”
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Time Series Forecasting Method Based on Multi-Scale Feature Fusion and Autoformer by Xiangkai Ma, Huaxiong Zhang

“…Based on multi-scale convolutional operations, a multi-scale feature fusion network is proposed, combined with date–time encoding to build the MD–Autoformer time series forecasting model, which enhances the model’s ability to capture information at different scales. …”
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