Wood Panel Defect Detection Based on Improved YOLOv8n by Rui Li, Shilu Zhong, Xuemei Yang

“…The loss function was optimized to improve detection accuracy and convergence speed. …”
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A Follow-Up Risk Identification Model Based on Multi-Source Information Fusion by Shuwei Guo, Yunyu Bo, Jie Chen, Yanan Liu, Jiajia Chen, Huimin Ge

“…Results show improved accuracy in car-following risk identification, with the optimized AutoEncoder_LR performing best at 91.33% for risk presence and 70.14% for risk levels. …”
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Measuring Catastrophic Forgetting in Cross-Lingual Classification: Transfer Paradigms and Tuning Strategies by Boshko Koloski, Blaz Skrlj, Marko Robnik-Sikonja, Senja Pollak

“…While both strategies have been studied, their effects on encoder-based models for classification tasks remain underexplored. …”
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DLLabelsCT: Annotation tool using deep transfer learning to assist in creating new datasets from abdominal computed tomography scans, case study: Pancreas. by Henrik Mustonen, Antti Isosalo, Minna Nortunen, Mika Nevalainen, Miika T Nieminen, Heikki Huhta

“…The tool accelerates annotation by 3.4 times compared to a completely manual annotation method. …”
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An investigation of simple neural network models using smartphone signals for recognition of manual industrial tasks by Tacjana Niksa‑Rynkiewicz, Panorios Benardos, Anna Witkowska, George-Christopher Vosniakos

“…In particular, simpler Feedforward Neural Networks (FNN) are focused on with an aim to optimize computational performance without compromising accuracy. …”
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Text intelligent correction in English translation: A study on integrating models with dependency attention mechanism. by Yutong Liu, Shile Zhang

“…During model training, the Adam optimization algorithm is employed, and the model's performance is enhanced by introducing a customized dependency self-attention mechanism for parameter optimization. …”
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Mutual Information Neural-Estimation-Driven Constellation Shaping Design and Performance Analysis by Xiuli Ji, Qian Wang, Liping Qian, Pooi-Yuen Kam

“…Innovatively, we first introduce the MINE module to effectively estimate and maximize MI through backpropagation, without clear knowledge of the channel state information. Then, we train encoder and probability generator networks with different signal-to-noise ratios to optimize the distribution locations and probabilities of the points, respectively. …”
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Research on Park Perception and Understanding Methods Based on Multimodal Text–Image Data and Bidirectional Attention Mechanism by Kangen Chen, Xiuhong Lin, Tao Xia, Rushan Bai

“…Furthermore, using the SHapley Additive exPlanations (SHAP) method, this study identified the key factors influencing visitors’ emotional experiences, such as “water”, “green”, and “sky”, providing a scientific basis for park management and optimization.…”
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A Hybrid Compact Convolutional Transformer with Bilateral Filtering for Coffee Berry Disease Classification by Biniyam Mulugeta Abuhayi, Andras Hajdu

“…The CCT model combines parallel convolutional branches for hierarchical feature extraction with a transformer encoder to capture long-range dependencies, enabling high performance on limited data. …”
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Fusion ConvLSTM-Net: Using Spatiotemporal Features to Increase Residential Load Forecast Horizon by Abhishu Oza, Dhaval K. Patel, Bryan J. Ranger

“…To make the most of these energy sources, optimizing the generation, storage, and distribution of energy can be enhanced with accurate forecasts of future energy consumption. …”
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Adaptive delta modulation method for arbitrary adaptation coefficients in the sensor network of the mobile ECG monitoring by О. В. Тимченко, В. І. Лозинський

“…The adaptation coefficient of this method is equal to 2, which is relevant with its convenience for hardware implementation. However, the optimality of its value for reducing the quantization error of the adaptive delta encoder was not considered. …”
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LSV-MAE: A Masked-Autoencoder Pre-Training Approach for Large-Scale 3D Point Cloud Data by Nuo Cheng, Chuanyu Luo, Han Li, Sikun Ma, Shengguang Lei, Pu Li

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Cacography based Ransomware Email Phishing Attack Prevention using Language Pack Tuned Transformer Language Model by S. Abiramasundari, V. Ramaswamy

“…Next, the proposed classification algorithms are (i) Lyrebird Optimization Algorithm—Long Short-Term Memory (LOA-LSTM), (ii) Hippopotamus Optimization (HO)-Gated Recurrent Neural Network (HO-GRU) and (iii) Meerkat Optimization Algorithm-Bidirectional Long Short-Term Memory (MOA-BiLSTM) which are used for REP classification based on tokenized text. …”
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Power Load Data Completion Method Based on Integrated Graph Convolutional Variational Transformer by YAN Li, HU Hailin, SHI Lei, WU Qinzheng, LÜ Tianguang, XU Yingdong, ZHANG Wenbin, WANG Gaozhou

“…In addition， an improved whale optimization algorithm （WOA） is introduced to optimize the network model hyperparameters and improve the completion accuracy and applicability of the model. …”
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A Comprehensive Framework for Transportation Infrastructure Digitalization: TJYRoad-Net for Enhanced Point Cloud Segmentation by Zhen Yang, Mingxuan Wang, Shikun Xie

“…The proposed method addresses the challenge of accurately capturing the current state of infrastructure while minimizing redundancy and optimizing computational efficiency. A key innovation is the development of the TJYRoad-Net model, which achieves over 85% mIoU segmentation accuracy by including a traffic feature computing (TFC) module composed of three critical components: the Regional Coordinate Encoder (RCE), the Context-Aware Aggregation Unit (CAU), and the Hierarchical Expansion Block. …”
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A Hierarchical Reinforcement Learning Framework for Multi-Agent Cooperative Maneuver Interception in Dynamic Environments by Qinlong Huang, Yasong Luo, Zhong Liu, Jiawei Xia, Ming Chang, Jiaqi Li

“…To address the challenges of real-time decision-making and resource optimization in multi-agent cooperative interception tasks within dynamic environments, this paper proposes a hierarchical framework for reinforcement learning-based interception algorithm (HFRL-IA). …”
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Causation Analysis of Marine Traffic Accidents Using Deep Learning Approaches: A Case Study from China’s Coasts by Zelin Zhao, Xingyu Liu, Lin Feng, Manel Grifoll, Hongxiang Feng

“…In response to the increasing frequency of maritime traffic accidents along China’s coast, this study develops an accident-cause analysis framework that integrates an optimized Bidirectional Encoder Representations from Transformers (BERT) with a Bidirectional Long Short-Term Memory network (BiLSTM), combined with the Apriori association rule algorithm. …”
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Forecasting formation density from well logging data based on machine learning model by Xiankang Cheng, Haoyu Zhang, Haoyu Zhang

“…The reason for adopting the integrated structure is to enhance prediction accuracy and robustness through collaborative optimization of multiple models. The CNN mainly extracts feature regions of interest and Transformer encoder is utilized to assign high weights to the regions of interest. …”
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Stepper Motor Position Control Using PD and MPC Algorithms Embedded in Programmable Logic Controller by Anshul Jaswal, Ma'moun Abu-Ayyad, Yash Lad, Anilchandra Attaluri

“…In addition, this study compares the result of MPC algorithm with traditional control strategies, such as PD. …”
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Design of agricultural question answering information extraction method based on improved BILSTM algorithm by Ruipeng Tang, Jianbu Yang, Jianxun Tang, Narendra Kumar Aridas, Mohamad Sofian Abu Talip

“…This study improves the accuracy of the agricultural information recommendation system from the perspective of information extraction. Compared with other work that is done from the perspective of recommendation algorithm optimization, it is more innovative; it helps to understand the semantics and contextual relationships in agricultural question and answer, which improves the accuracy of agricultural information recommendation systems. …”
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