MCFTNet: Multimodal Cross-Layer Fusion Transformer Network for Hyperspectral and LiDAR Data Classification by Wei Huang, Tianren Wu, Xueyu Zhang, Liangliang Li, Ming Lv, Zhenhong Jia, Xiaobin Zhao, Hongbing Ma, Gemine Vivone

“…This enables the model to better integrate information from different layers, enhancing both its stability and performance. …”
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A depth-wise separable VGG19-capsule network for enhanced bell pepper and grape leaf disease classification with ensemble activation by Midhun P Mathew, Sudheep Elayidom, Jagathy Raj V P, Abubeker K M

“…The novel contribution lies in the enhanced VGG19 architecture, incorporating depth-wise separable convolution, batch normalization, and a 40% dropout by introducing convolutional layers before the primary capsule layer. …”
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Fine-Grained Recognition of Fidgety-Type Emotions Using Multi-Scale One-Dimensional Residual Siamese Network by Jiu SUN, Junxin ZHU, Jun SHAO

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A Lightweight Network for Water Body Segmentation in Agricultural Remote Sensing Using Learnable Kalman Filters and Attention Mechanisms by Dingyi Liao, Jun Sun, Zhiyong Deng, Yudong Zhao, Jiani Zhang, Dinghua Ou

“…However, the spectral noise caused by complex light and shadow interference and water quality differences, combined with the diverse shapes of water bodies and the high computational cost of image processing, severely limits the accuracy of water body recognition in agricultural watersheds. …”
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A Cluster-based Optimal Scheduling Strategy for Electric Vehicles Considering User Participation by HAN Yan, DING Xiying, CHENG Kun, LI Xiaodong

“…Multilayer perceptron neural network is adopted to predict power load and obtain peak difference. The electric vehicle cluster classification network based on convolutional neural network is trained by using a large number of vehicle information and considering vehicle owner intention to classify the vehicle peak shaving participation, and quickly determine the total electricity involved in peak shaving. …”
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Time Series Forecasting for Air Quality with Structured and Unstructured Data Using Artificial Neural Networks by Kenneth Chan, Paul Matthews, Kamran Munir

“…However, the concentration of certain pollutants, such as PM_2.5 and PM₁₀, can be visually significant when there is a marked difference in their levels. Consequently, air quality from meteorological cameras can be estimated and integrated with data from monitoring stations to generate an air quality forecast. …”
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A novel PV power prediction method with TCN-Wpsformer model considering data repair and FCM cluster by Tong Yang, Minan Tang, Hanting Li, Hongjie Wang, Chuntao Rao

“…The comparison is made through 11 models, and the R squared of this model is above 99% while different data volume and different power station data. …”
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Detection of the origin of wolfberry based on electronic nose and electronic tongue combined with LSTM-AM-M1DCNN by MA Zeliang, LIU Yaqian, CHENG Qifeng, WANG Pingping, YANG Tianxing, DU Gang

“…It is suitable for processing data collected by the electronic nose and tongue and can effectively and accurately discriminate wolfberries from five different origins.…”
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Enhancing agricultural research with an Attention-Based Hybrid Model for precise classification of rice varieties by Nuzhat Noor Islam Prova

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A Deep-Learning Workflow for CORONA-Based Historical Land Use Classifications by Wei Liu, Shuai Li, Di Fan, Yixin Wen, Austin Madson, Jessica Mitchell, Yaqian He, Di Yang

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Multi-Dimensional Lithology Identification Method Based on Microresistivity Image Logging by LIU Juan, MIN Xuanlin, QI Zhongli, YI Jun, LAI Fuqiang, ZHOU Wei

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High-Density Surface EMG Decomposition: Achievements, Challenges, and Concerns by Maoqi Chen, Ping Zhou

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DA-ResNeXt50 method for radio frequency fingerprint identification based on time-frequency and bispectral feature fusion by CHEN Mengdi, ZHANG Wei, SHEN Lei, LEI Fuqiang, ZHANG Jiafei

“…Borrowing from the idea of dense connection, each layer of the four-layer residual unit was directly connected to all previous layers, promoting feature reuse and transmission, which enabled it to better capture subtle differences between classes. Finally, the asymmetric convolution block (ACBlock) was used to replace the 3×3 convolution in the last residual unit of the model. …”
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A Comparison of Two Neural Network Based Methods for Human Activity Recognition by saeedeh zebhi, Seyed Mohammad Taghi AlModaressi, Vahid Abootalebi

“…In this paper, two different methods of human activity recognition based on video signals are introduced. …”
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Exploring single-head and multi-head CNN and LSTM-based models for road surface classification using on-board vehicle multi-IMU data by Luis A. Arce-Saenz, Javier Izquierdo-Reyes, Rogelio Bustamante-Bello

“…Various model architectures were tested, incorporating IMU data from different positions and utilizing both acceleration and angular velocity features. …”
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Brain tumor segmentation using deep learning: high performance with minimized MRI data by Jacky Huang, Banu Yagmurlu, Powell Molleti, Richard Lee, Abigail VanderPloeg, Humaira Noor, Rohan Bareja, Yiheng Li, Michael Iv, Haruka Itakura

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Can machine learning distinguish between elite and non-elite rowers? by Orten Kristine Fjellkårstad, Helgesen Sander Elias Magnussen, Chen Bihui, Baselizadeh Adel, Torresen Jim, Herrebrøden Henrik

“…In the current study, we employed various deep learning frameworks, including Gated Recurrent Unit networks (GRUs), Convolutional Neural Networks (CNNs), and Multi-Layer Perceptrons (MLPs), to search for differences between elite and non-elite rowers using a rowing ergometer. …”
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Kidney Disease Segmentation and Classification Using Firefly Sigma Seeker and MagWeight Rank Techniques by Dilovan Asaad Zebari

“…Through extensive experimentation and evaluation on kidney disease segmentation datasets, a comparative analysis of different architectures was conducted in terms of segmentation accuracy, computational efficiency, and scalability. …”
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Robust Radio Frequency Fingerprinting With Signal Denoising and Stacked Multivariate Ensemble Learning for Secure Wireless Communications by Syed Usman Ali Shah, Muhammad Usama Zahid, Syed Abuzar H Shah, Saeed Ur Rehman, Dan Komosny

“…The proposed architecture employs lightweight, homogeneous Convolutional Neural Networks (CNNs) optimized for rapid model training and fast inference, ensuring computational efficiency without sacrificing accuracy. …”
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Research on event extraction methods for medical by Yuekun MA, Moxiao CUI

“…Firstly, multi-dimensional local feature information of the text was extracted by combining convolutional neural networks with different filter window sizes, while the global feature information of the text was captured using bidirectional long short-term memory networks. …”
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