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

“…ObjectiveTo achieve rapid detection of the origin of wolfberry.MethodsA rapid discrimination method for the origin of wolfberry was proposed based on an electronic nose and tongue system using a Long Short-Term Memory network-Attention Mechanism-Multi-scale one-Dimensional Convolutional Neural Network (LSTM-AM-M1DCNN) model. …”
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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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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

“…By leveraging these techniques, the parallel convolutional layers are specifically tailored for kidney disease segmentation tasks. …”
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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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Multi-stream feature fusion of vision transformer and CNN for precise epileptic seizure detection from EEG signals by Qi Li, Wei Cao, Anyuan Zhang

“…Methods Our study proposes an epilepsy detection model, CMFViT, based on a Multi-Stream Feature Fusion (MSFF) strategy that fuses a Convolutional Neural Network (CNN) with a Vision Transformer (ViT). …”
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A systematic review of multimodal fake news detection on social media using deep learning models by Maged Nasser, Noreen Izza Arshad, Abdulalem Ali, Hitham Alhussian, Faisal Saeed, Aminu Da'u, Ibtehal Nafea

“…The volume of data circulating from online sources is growing rapidly and comprises both reliable and unreliable information published through many different sources. Researchers are making plausible efforts to develop reliable methods for detecting and eliminating fake web news. …”
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Field-grown tomato yield estimation using point cloud segmentation with 3D shaping and RGB pictures from a field robot and digital single lens reflex cameras by B. Ambrus, G. Teschner, A.J. Kovács, M. Neményi, L. Helyes, Z. Pék, S. Takács, T. Alahmad, A. Nyéki

“…By comparing the measured and estimated yield, the average difference for DSLR camera images was more favorable at 3.42 kg.…”
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FA-FENet: A Feature Attention Front-End Network Based on a Lightweight CNN Architecture for Recognizing Abnormal Underwater Illegal Fishing Behavior by Xiang-Rui Huang, Liang-Bi Chen

“…Herein, we propose a feature attention front-end network (FA-FENet), a novel end-to-end convolutional neural network (CNN) architecture that differs from previous methods in that it allows flexible integration with various backbone networks. …”
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Towards Self-Conscious AI Using Deep ImageNet Models: Application for Blood Cell Classification by Mohamad Abou Ali, Fadi Dornaika, Ignacio Arganda-Carreras

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A Hybrid Strategy-Improved SSA-CNN-LSTM Model for Metro Passenger Flow Forecasting by Jing Liu, Qingling He, Zhikun Yue, Yulong Pei

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Adaptive GCN and Bi-GRU-Based Dual Branch for Motor Imagery EEG Decoding by Yelan Wu, Pugang Cao, Meng Xu, Yue Zhang, Xiaoqin Lian, Chongchong Yu

“…Furthermore, combining Bi-GRU and Multi-Head Attention (MHA) captures the temporal dependencies across different time segments to extract deep time–spectral features. …”
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