YOLO-DKM: A Flame and Spark Detection Algorithm Based on Deep Learning by Linpo Shang, Xufei Hu, Zijian Huang, Qiang Zhang, Zhiyu Zhang, Xin Li, Yanzuo Chang

“…And integrate DSConv into the C2f module, relying on dynamic characteristics to adaptively adjust convolution operations according to different scene features for more flexible local region feature extraction, capturing local features of flames and sparks. …”
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Enhanced Skin Lesion Classification Using Deep Learning, Integrating with Sequential Data Analysis: A Multiclass Approach by Azmath Mubeen, Uma N. Dulhare

“…In dermatological research, accurately identifying different types of skin lesions, such as nodules, is essential for early diagnosis and effective treatment. …”
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Comparative Study of CNN Architectures for Brain Tumor Classification Using MRI: Exploring GradCAM for Visualizing CNN Focus by Areli Chinga, Wilden Bendezu, Antonio Angulo

“…This study aims to refine the diagnosis of brain tumors using convolutional neural network algorithms. Currently, diagnostic accuracy is limited, therefore, our approach uses five different CNN architectures to accurately identify and classify affected brain regions, specifically glioma, meningioma, or pituitary tumors. …”
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DoS and DDoS Attack Detection in IoT Infrastructure using Xception Model with Explainability by Nelly Elsayed, Zag ElSayed, Ahmed Abdelgawad

“…Thus, this paper proposes utilizing convolutional neural network-based transfer learning to detect DoS and DDoS attacks from converted network traffic data into images. …”
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Algae-Mamba: A Spatially Variable Mamba for Algae Extraction From Remote Sensing Images by Yaoteng Zhang, Shuaipeng Wang, Yanlong Chen, Shiqing Wei, Mingming Xu, Shanwei Liu

“…To address the common misclassification between sargassum and ulva under limited spectral data, Algae-Mamba incorporates the normalized difference water index (NDWI) to enhance semantic richness. …”
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Timing data visualization: tactical intent recognition and portable framework by SONG Yafei, LI Lemin, QUAN Wen, NI Peng, WANG Ke

“…Curve filtering technology effectively reduced redundancy in numerous time-domain features, model parameters, and training time, an enhanced Gramian angular field (GAF) method was proposed to encode time series into images, enhancing the feature extraction capabilities of convolutional neural networks. The EfficientNetV2 network was adept at processing intent images and could serve as a pre-trained model, facilitating transfer learning across different systems. …”
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Timing data visualization: tactical intent recognition and portable framework by SONG Yafei, LI Lemin, QUAN Wen, NI Peng, WANG Ke

“…Curve filtering technology effectively reduced redundancy in numerous time-domain features, model parameters, and training time, an enhanced Gramian angular field (GAF) method was proposed to encode time series into images, enhancing the feature extraction capabilities of convolutional neural networks. The EfficientNetV2 network was adept at processing intent images and could serve as a pre-trained model, facilitating transfer learning across different systems. …”
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Intelligent Fault Diagnosis of Inter-Turn Short Circuit Faults in PMSMs for Agricultural Machinery Based on Data Fusion and Bayesian Optimization by Mingsheng Wang, Wuxuan Lai, Hong Zhang, Yang Liu, Qiang Song

“…Firstly, synchronizing data from different signals extracted by different devices presents a significant challenge. …”
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Two-stage augmentation for detecting malignancy of BI-RADS 3 lesions in early breast cancer by Huanhuan Tian, Li Cai, Yu Gui, Zhigang Cai, Xianfeng Han, Jianwei Liao, Li Chen, Yi Wang

“…Abstract Objectives In view of inherent attributes of breast BI-RADS 3, benign and malignant lesions are with a subtle difference and the imbalanced ratio (with a very small part of malignancy). …”
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Classification of Hybrid and Peking Duck DOD Varieties Based on Feather Images Using CNN by Khoironi, I Wayan Rangga Pinastawa

“…In this study, a deep learning approach with the Convolutional Neural Network (CNN) algorithm was applied to classify DOD varieties based on feather images. …”
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Evaluation of Dose Calculation Algorithms Accuracy for ISOgray Treatment Planning System in Motorized Wedged Treatment Fields by Sajjad Raghavi, Hamid-Reza Sadoughi, Mohammad Ehsan Ravari, Marziyeh Behmadi

“…Background: Different dose calculation methods vary in accuracy and speed. …”
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Efficient Brain Tumor Segmentation for MRI Images Using YOLO-BT by Mengying Xiong, Aiping Wu, Yue Yang, Qingqing Fu

“…The D-LKA mechanism is introduced into the C3k2 structure, and the large convolution kernel is used to process complex image information to enhance the model’s ability to characterize different scales and irregular tumors. …”
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The Detection of Fake Text News using a Dense-based 1D-CNN Deep Learning Algorithm by Khalid Abood Kamel, Jumana Waleed

“…compared to the previous different methods to solve this problem, including some common ‎deep-learning methods. …”
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Rail Transit Prediction Based on Multi-View Graph Attention Networks by Li Wang, Xin Wang, Jiao Wang

“…Multiple nodes and various associations such as different types of stations and lines in rail transit always exist at the same time. …”
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Adaptive clustering federated learning via similarity acceleration by Suxia ZHU, Binke GU, Guanglu SUN

“…In order to solve the problem of model performance degradation caused by data heterogeneity in the federated learning process, it is necessary to consider personalizing in the federated model.A new adaptively clustering federated learning (ACFL) algorithm via similarity acceleration was proposed, achieving adaptive acceleration clustering based on geometric properties of local updates and the positive feedback mechanism during clients federated training.By dividing clients into different task clusters, clients with similar data distribution in the same cluster was cooperated to improve the performance of federated model.It did not need to determine the number of clusters in advance and iteratively divide the clients, so as to avoid the problems of high computational cost and slow convergence speed in the existing clustering federation methods while ensuring the performance of models.The effectiveness of ACFL was verified by using deep convolutional neural networks on commonly used datasets.The results show that the performance of ACFL is comparable to the clustered federated learning (CFL) algorithm, it is better than the traditional iterative federated cluster algorithm (IFCA), and has faster convergence speed.…”
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Spectroscopic measurement of near-infrared soil pH parameters based on GhostNet-CBAM. by Jianguo Zhu, Wenjin Wang, Peng Tian

“…In this paper, we propose a neural network algorithm using Ghostnet combined with Convolutional Block Attention Module (CABM) to realize the near-infrared (NIR) PH spectral measurement of soil. …”
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Deep Learning-Based Video Anomaly Detection Using Optimised Attention-Enhanced Autoencoders by Anjali S, Don S

“…Through the reconstruction of normal patterns and the computation of reconstruction error in relation to ground truth, convolutional autoencoders detect anomalies. Frames with errors above a threshold are flagged as abnormal. …”
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MFF-Net: A Lightweight Multi-Frequency Network for Measuring Heart Rhythm from Facial Videos by Wenqin Yan, Jialiang Zhuang, Yuheng Chen, Yun Zhang, Xiujuan Zheng

“…In addition, in order to help the network extract the characteristics of different modal signals effectively, we designed a temporal multiscale convolution module (TMSC-module) and spectrum self-attention module (SSA-module). …”
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Improved YOLOv8 Algorithm was Used to Segment Cucumber Seedlings Under Complex Artificial Light Conditions by Duokuo Zhang, Na Li, Mingfu Zhao, Kun Xu

“…First, the C2f module in the YOLOv8 backbone network is optimized by replacing the bottleneck with the multi-scale feature module (MSFM) we designed. The convolution kernels of different sizes are employed to capture features at multiple scales in the image, thereby processing target and background information more effectively. …”
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An RNN-CNN-Based Parallel Hybrid Approach for Battery State of Charge (SoC) Estimation Under Various Temperatures and Discharging Cycle Considering Noisy Conditions by Md. Shahriar Nazim, Md. Minhazur Rahman, Md. Ibne Joha, Yeong Min Jang

“…In addition, EVs operate in different environmental conditions with different driving styles, which also cause inaccurate SoC estimation resulting in reduced reliability and performance of battery management systems (BMSs). …”
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