A New Efficient Hybrid Technique for Human Action Recognition Using 2D Conv-RBM and LSTM with Optimized Frame Selection by Majid Joudaki, Mehdi Imani, Hamid R. Arabnia

“…To address these limitations, we propose a novel model combining a two-dimensional convolutional restricted Boltzmann machine (2D Conv-RBM) with a long short-term memory (LSTM) network. …”
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Adaptive Token Mixer for Hyperspectral Image Classification by Shuhan Lei, Meng Zhang, Yuhang Wang, Nan Tang, Ni Jia, Lihua Fu

“…In addition, we introduce a cross-shaped convolutional operator (COSTCO) to enhance local spatial feature extraction. …”
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Temporal Segment Method in Sign Word Recognition Using a Pretrained CNN-LSTM Network by Seungju Lee, Irina Polyakova

“…Results demonstrated that applying TSN significantly reduced computational costs: training time was reduced by a factor of 2.173, GPU RAM usage decreased by a factor of 0.5514, and system memory usage by a factor of 1.027. …”
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Hybrid-CID: Securing IoT with Mongoose Optimization by S. Merlin Sheeba, R. S. Shaji

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Hybrid CNN-GRU Models for Improved EEG Motor Imagery Classification by Mouna Bouchane, Wei Guo, Shuojin Yang

“…The first model combines a shallow convolutional neural network and a gated recurrent unit (CNN-GRU), while the second incorporates a convolutional neural network with a bidirectional gated recurrent unit (CNN-Bi-GRU). …”
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ABA-IDS: Attention-Based Autoencoder for Intrusion Detection in Assistive Mobility Robotic Network by Daniel Ayo Oladele, Elisha Didam Markus

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Automated Concrete Bridge Deck Inspection Using Unmanned Aerial System (UAS)-Collected Data: A Machine Learning (ML) Approach by Rojal Pokhrel, Reihaneh Samsami, Saida Elmi, Colin N. Brooks

“…According to the National Bridge Inventory (NBI) and the Federal Highway Administration (FHWA), the cost to repair U.S. bridges was recently estimated at approximately USD 164 billion. …”
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Deep learning approach for automated hMPV classification by Sivarama Prasad Tera, Ravikumar Chinthaginjala, Irum Shahzadi, Priya Natha, Safia Obaidur Rab

“…This reduction in computational cost makes the model suitable for deployment in resource-constrained healthcare environments, where computing power and infrastructure may be limited.…”
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A novel hybrid neural network of fluid-structure interaction prediction for two cylinders in tandem arrangement by Yanfang Lyu, Yunyang Zhang, Zhiqiang Gong, Xiao Kang, Wen Yao, Yongmao Pei

“…Fluid-structure interaction (FSI) in multibody systems, a non-negligible phenomenon in engineering applications, has been extensively studied via traditional experimental and simulation methods with high cost and time consumption. Deep learning has shown promise in improving computing efficiency while ensuring modelling accuracy in FSI analysis. …”
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Comparative Study of Person Re-Identification Techniques Based on Deep Learning Models by Mossaab Idrissi Alami, Abderrahmane Ez-zahout, Fouzia Omary

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DSGAU: Dual-Scale Graph Attention U-Nets for Hyperspectral Image Classification With Limited Samples by Hongzhuang Ji, Leying Song, Zhaohui Xue, Hongjun Su

“…Graph convolutional networks (GCNs) exhibit remarkable capabilities in hyperspectral image (HSI) classification tasks, primarily due to their ability to establish long-range pixel correlations. …”
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Estimating Automobile Crash Characteristics from Images using Deep Learning by Daniel Silver, Hardik Manek, Matthew Kay, Paul Travis

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Acoustic fault diagnosis of traction motor bearing based on fusion feature by YANG Gang, WEI Yuqian, LI Fu

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Pig behavior recognition and disease warning based on compressed sensing and long-short term memory network by Ren Wang, Mingdong Zhao

“…The improved k-means clustering algorithm is combined with convolutional neural network and long and short term memory network to provide early warning for pig diseases. …”
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YOLO-I3D: Optimizing Inflated 3D Models for Real-Time Human Activity Recognition by Ruikang Luo, Aman Anand, Farhana Zulkernine, Francois Rivest

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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

“…In this work, to improve the accuracy of photovoltaic power prediction, a TCN-Wpsformer (temporal convolutional network-window probability sparse Transformer) day-ahead photovoltaic power prediction model based on combining data restoration and FCM (fuzzy C means) cluster is proposed. …”
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Short-Term Telephone-Traffic Prediction of Power Grid Customer Service Based on Adaboost-CNN by QIN Hao, SU Liwei, WU Guangbin, JIANG Chongying, XU Zhipeng, KANG Feng, TAN Huochao, ZHANG Yongjun

“…Accurate power supply service traffic prediction not only improves the quality of power customer service, but also effectively reduces the cost of customer service personnel. Therefore, this paper proposes a short-term traffic prediction method for power grid based on Adaboost and convolutional neural network (Adaboost-CNN) and a value-added service correction method. …”
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From Simulation to Reality: Transfer Learning for Automating Pseudo‐Labeling of Real and Infrared Imagery by Jeffrey Choate, Derek Worth, Scott L. Nykl, Clark Taylor, Brett Borghetti, Christine Schubert Kabban, Ryan Raettig

“…Training a convolutional neural network (CNN) for real‐world applications is challenging due to the requirement of high‐quality labeled imagery. …”
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Enhancing skin lesion classification: a CNN approach with human baseline comparison by Deep Ajabani, Zaffar Ahmed Shaikh, Amr Yousef, Karar Ali, Marwan A. Albahar

“…This study presents an augmented hybrid approach for improving the diagnosis of malignant skin lesions by combining convolutional neural network (CNN) predictions with selective human interventions based on prediction confidence. …”
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Research on an hourly heat load forecasting model for district heating systems based on heterogeneous model fusion by Tieliu Jiang, Wenyue Liu, Jianqing Lin, Xu Jin, Zhongyan Liu

“…This model can provide high-precision guidance for thermal scheduling, facilitating optimization of energy losses and control of operational costs.…”
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