Synergizing BRDF correction and deep learning for enhanced crop classification in GF-1 WFV imagery by Yuanwei Chen, Yang Li, Runze Li, Chongzheng Guo, Jilin Li

“…Three typical deep learning architectures—Feature Pyramid Network (FPN), Fully Convolutional Network (FCN), and UNet, are employed to perform classification experiments. …”
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RecurrentOcc: An Efficient Real-Time Occupancy Prediction Model with Memory Mechanism by Zimo Chen, Yuxiang Xie, Yingmei Wei

“…The Scene Memory Gate selectively retains valuable information from historical features and recurrently updates the historical feature map, enhancing temporal fusion performance. …”
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MalFormer: A Novel Vision Transformer Model for Robust Malware Analysis by In-Woong Jeong, Han-Ju Lee, Gwang-Nam Kim, Seok-Hwan Choi

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Leveraging explainable artificial intelligence for early detection and mitigation of cyber threat in large-scale network environments by G. Nalinipriya, S. Rama Sree, K. Radhika, E. Laxmi Lydia, Faten Khalid Karim, Mohamad Khairi Ishak, Samih M. Mostafa

“…A Sparse Denoising Autoencoder (SDAE) model recognizes and classifies cyber threats. Additionally, the Hiking Optimization Algorithm (HOA) is employed to fine-tune the hyperparameters of the SDAE model. …”
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End-to-End Multi-Modal Speaker Change Detection with Pre-Trained Models by Alymzhan Toleu, Gulmira Tolegen, Alexandr Pak, Jaxylykova Assel, Bagashar Zhumazhanov

“…In this work, we propose a multi-modal speaker change detection (SCD) approach with focal loss, which integrates both audio and text features to enhance detection performance. The proposed approach utilizes pre-trained large-scale models for feature extraction and incorporates a self-attention mechanism to optimize useful features related to speaker change. …”
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Nitrate Content in Open Field Spinach, Applicative Case for Hyperspectral Reflectance Data by Walter Polilli, Angelica Galieni, Fabio Stagnari

“…While the majority voting approach did not improve performance (Acc 0.82), the stacked ensemble models reached Acc 0.88. …”
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MASNet: mixed attention Siamese network for visual object tracking by Jianwei Zhang, Zhichen Zhang, Huanlong Zhang, Jingchao Wang, He Wang, Menya Zheng

“…Most Siamese-based trackers adopt correlation operation to perform similarity matching on feature fusion of template branch and search branch. …”
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SBNNR: Small-Size Bat-Optimized KNN Regression by Rasool Seyghaly, Jordi Garcia, Xavi Masip-Bruin, Jovana Kuljanin

“…For this reason, in some cases, low-performance, overfitting models are developed for small-scale data. …”
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A Novel Long Short-Term Memory-Based Approach for Microgrid Fault Detection and Classification Using the Wavelet Scattering Transform by Naema M. Mansour, Abdelazeem A. Abdelsalam, Ibrahim A. Awaad

“…All simulations were performed in MATLAB, which served as the platform for modeling the CERTS microgrid, configuring the WST, and implementing the LSTM network. …”
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Coronary Artery Disease Detection Based on a Novel Multi-Modal Deep-Coding Method Using ECG and PCG Signals by Chengfa Sun, Changchun Liu, Xinpei Wang, Yuanyuan Liu, Shilong Zhao

“…Final CAD classification is conducted by combining support vector machine and optimal multi-modal features. The experiment is validated on 199 simultaneously recorded ECG and PCG signals from non-CAD and CAD subjects, and achieves high performance with accuracy, sensitivity, specificity and f1-score of 98.49%, 98.57%,98.57% and 98.89%, respectively. …”
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RGB-FIR Multimodal Pedestrian Detection with Cross-Modality Context Attentional Model by Han Wang, Lei Jin, Guangcheng Wang, Wenjie Liu, Quan Shi, Yingyan Hou, Jiali Liu

“…To achieve full day detection performance, multimodal YOLO models based on RGB-FIR image pairs have become a research hotspot. …”
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HY-Deepnet : A new Optimal Deep transfer learning empowered framework for an autonomous Alzheimer’s disease detection and diagnosis system by S. Veluchamy, R. Bhuvaneswari, K. Ashwini, Samah Alshathri, Walid El-Shafai

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Sensor-less Vector Control of a Novel Axial Field Flux-Switching Permanent-Magnet Motor with High-Performance Current Controller by Javad Rahmani Fard

“…Based on the vector control method, the mathematical model of the AFFSSPM is derived and the operating performance of the AFFSSPM in the overall operating region is investigated.A novel control method for the AFFSSPM drive system, including the id =0, maximum torque per ampere, constant flux linkage, unity power factor control and flux-weakening strategy, is proposed. …”
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Detecting early gastrointestinal polyps in histology and endoscopy images using deep learning by Intissar Dhrari Hajsalem, Yassine Ben Ayed

“…Nevertheless, a lot of current technologies are still insufficient to detect tumors, which is why we created an approach using advanced method to identify polyps.MethodsOur three-stage deep learning-based method requires constructing an Encoder-Decoder Network (EDN) to determine the Region of Interest (ROI) in preprocessing, feature selection with pretrained models such as VGG16, VGG19, ResNet50 and InceptionV3, and Support Vector Machine (SVM) classifier to separate affected individuals from normal ones during the classification stage. …”
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LASSO-mCGA: Machine Learning and Modified Compact Genetic Algorithm-Based Biomarker Selection for Breast Cancer Subtype Classification by Nimisha Ghosh, Sankar Kumar Mridha, Rourab Paul

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Machine learning-based risk of fall estimation using insole with force sensors while performing a sequence of activities in the TUG test by Clinton Enow Tabi, Johannes C. Ayena, Martin J.-D. Otis

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Using the Ship-Gram Model for Japanese Keyword Extraction Based on News Reports by Miao Teng

“…The experimental results show that the proposed keyword extraction algorithm can improve the performance by a maximum of 6.45% and 20.36% compared with the existing word frequency statistics and graph model methods, respectively; MF-Rank can achieve a maximum performance improvement of 1.76% compared with PW-TF.…”
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U-Net-based VGG19 model for improved facial expression recognition by Xiaohu ZHAO, Jingyi ZHANG, Mingzhi JIAO, Lixun XIE, Lanfei WANG, Weiqing SUN, Di ZHANG

“…In conclusion, integrating the U-Net architecture and enhanced SEAttention module into the VGG19 network led to significant advancements in facial expression recognition. The improved model not only boosts performance in terms of feature extraction and fusion but is also adept in solving the pressing problems of parameter size and computational efficiency. …”
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Detecting small seamounts in multibeam data using convolutional neural networks by Tobias Ziolkowski, Colin W. Devey, Agnes Koschmider

“…A hyperparameter optimization study determined the optimal U-Net configuration, achieving a Dice Coefficient of 0.8274 and a Mean IoU of 0.7514. While the model performed well within the training dataset, cross-regional generalization remains challenging, with reduced accuracy observed in areas of highly variable seafloor morphology. …”
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A New Random Coefficient Autoregressive Model Driven by an Unobservable State Variable by Yuxin Pang, Dehui Wang

“…A novel random coefficient autoregressive model is proposed, and a feature of the model is the non-stationarity of the state equation. …”
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