Neural-field-based image reconstruction for bioluminescence tomography by Xuanxuan Zhang, Xu Cao, Jiulou Zhang, Lin Zhang, Guanglei Zhang

“…The proposed NF-based method establishes a transformation between the coordinate of an arbitrary spatial point and the source value of the point with a relatively light-weight multilayer perceptron, which has remarkable computational efficiency. Another simple neural network composed of two fully connected layers and a 1D convolutional layer is used to generate the neural features. …”
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Design of a Novel Fractional Whale Optimization-Enhanced Support Vector Regression (FWOA-SVR) Model for Accurate Solar Energy Forecasting by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Hafeez Anwar, Tariq Ali

“…The FWOA-SVR model is comprehensively evaluated against traditional SVR, Long Short-Term Memory (LSTM), and Backpropagation Neural Network (BPNN) models using training, validation, and testing datasets. …”
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Multimodal Multiobject Tracking by Fusing Deep Appearance Features and Motion Information by Liwei Zhang, Jiahong Lai, Zenghui Zhang, Zhen Deng, Bingwei He, Yucheng He

“…After that, we use Convolutional Neural Network (CNN) to learn the deep appearance features of objects and employ Kalman Filter to obtain the motion information of objects. …”
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Accelerating materials property prediction via a hybrid Transformer Graph framework that leverages four body interactions by Mohammad Madani, Valentina Lacivita, Yongwoo Shin, Anna Tarakanova

“…We propose a framework utilizing a Graph Neural Network with composition-based and crystal structure-based architectures, combined with a transfer learning scheme. …”
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Recycled integrated circuit detection using reliability analysis and machine learning algorithms by Udaya Shankar Santhana Krishnan, Kalpana Palanisamy

“…In this work, three machine learning methods, namely K‐means clustering, back propagation neural network (BPNN) and support vector machines (SVMs), are used to detect the recycled IC aged for a shorter period (1 day) with minimum data size. …”
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A Novel Technique for Handwritten Signature Recognition by Leila Boucerredj, Karima Kechroud, Bouaziz Noureddine, Abderrahmane Khechekhouche

“…This paper introduces a novel deep learning approach utilizing a convolutional neural network (CNN) architecture specifically designed for HSR. …”
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High-resolution hybrid TDM-CDM MIMO automotive radar by Zakaria Benyahia, Mostafa Hefnawi, Mohamed Aboulfatah, Hassan Abdelmounim, Jamal Zbitou

“…On the other hand, the DL-based scheme utilizes the SqueezeNet deep convolutional neural network (DCNN), which treats the angle, range, and Doppler estimations of the extracted targets as a multi-label classification problem. …”
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Temperature dynamics and mechanical properties analysis of carbon fiber epoxy composites radiated by nuclear explosion simulated light source by Lin Yuan, Jun Li, Boyu Wang, Xin Zhang, Weijie Zhu, Yang Liu, Haiyang Zhang, Xiaoxiang Han

“…This investigation employed an artificial light source to replicate the effects of nuclear explosion radiation and utilized a physical information neural network (PINN) to examine the temperature evolution and corresponding changes in the mechanical properties of carbon fiber/epoxy composites (CFEC). …”
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Interactive trajectory prediction for autonomous driving based on Transformer by R. Xu, J. Li, S. Zhang, L. Li, H. Li, G. Ren, X. Tang

“…The rationale underlying this approach lies in its seamless fusion of scene context modeling and multi-modal prediction within a neural network architecture. At the heart of this innovative framework resides the multi-headed attention mechanism, ingeniously deployed in both the agent attention layer and the scene attention layer. …”
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Unfolder: fast localization and image rectification of a document with a crease from folding in half by A.M. Ershov, D.V. Tropin, E.E. Limonova, D.P. Nikolaev, V.V. Arlazarov

“…The Unfolder algorithm allowed for a recognition error rate of 0.33, which is better than the advanced neural network methods DocTr (0.44) and DewarpNet (0.57). …”
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Fault Diagnosis of Gearbox in Multiple Conditions Based on Fine-Grained Classification CNN Algorithm by Pengcheng Jiang, Hua Cong, Jing Wang, Dongsheng Zhang

“…The use of the convolutional neural network for fault diagnosis has been a common method of research in recent years. …”
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Fast and low‐power leading‐one detectors for energy‐efficient logarithmic computing by Mohammad Saeed Ansari, Shyama Gandhi, Bruce F. Cockburn, Jie Han

“…The Mitchell logarithmic multiplier and a neural network are considered to further illustrate the practicality of the proposed designs.…”
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A multicenter study of neurofibromatosis type 1 utilizing deep learning for whole body tumor identification by Cheng-Jiang Wei, Yan Tang, Yang-Bai Sun, Tie-Long Yang, Cheng Yan, Hui Liu, Jun Liu, Jing-Ning Huang, Ming-Han Wang, Zhen-Wei Yao, Ji-Long Yang, Zhi-Chao Wang, Qing-Feng Li

“…To address privacy concerns, we utilized a lightweight deep neural network suitable for hospital deployment. The final model achieved an accuracy of 85.71% for MPNST diagnosis in the validation cohort and 84.75% accuracy in the independent test set, outperforming another classic two-step model. …”
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Segmentation Algorithm of Magnetic Resonance Imaging Glioma under Fully Convolutional Densely Connected Convolutional Networks by Jie Dong, Yueying Zhang, Yun Meng, Tingxiao Yang, Wei Ma, Huixin Wu

“…This work focused on the application value of magnetic resonance imaging (MRI) image segmentation algorithm based on fully convolutional DenseNet neural network (FCDNN) in glioma diagnosis. In this work, based on the fully convolutional DenseNet algorithm, a new MRI image automatic semantic segmentation method cerebral gliomas semantic segmentation network (CGSSNet) was established and was applied to glioma MRI image segmentation by using the BraTS public dataset as research data. …”
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Real-Time Quality Monitoring and Anomaly Detection for Vision Sensors in Connected and Autonomous Vehicles by Elena Politi, Charalampos Davalas, Christos Chronis, George Dimitrakopoulos, Dimitrios Michail, Iraklis Varlamis

“…On this basis we adopt a two-stage approach to validate the performance of the proposed methods against a baseline Convolutional Neural Network (CNN) in a controlled low-criticality environment, as well as in more complex real-world scenarios. …”
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Intelligent Classification of Stable and Unstable Slope Conditions Based on Landslide Movement by Long Tsang, Ali Ghorbani, Seyed Mohammad Hossein Khatami, Dmitrii Ulrikh

“…Three models of Tree, Adaboost and artificial neural network (ANN) were developed for classification into two categories, stable and unstable. …”
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Memory-driven deep-reinforcement learning for autonomous robot navigation in partially observable environments by Estrella Montero, Nabih Pico, Mitra Ghergherehchi, Ho Seung Song

“…The proposed method takes the relative states of humans within a limited FoV and sensor range as input into the neural network. The model employs a bidirectional gated recurrent unit as a temporal function to strategically incorporate the previous context of input sequences and facilitate the assimilation of the observations. …”
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Credit Card Fraud Detection through Parenclitic Network Analysis by Massimiliano Zanin, Miguel Romance, Santiago Moral, Regino Criado

“…We show how the inclusion of features extracted from the network data representation improves the score obtained by a standard, neural network-based classification algorithm and additionally how this combined approach can outperform a commercial fraud detection system in specific operation niches. …”
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Deteksi Dan Klasifikasi Hama Potato Beetle Pada Tanaman Kentang Menggunakan YOLOV8 by Daniel Geoffrey Manurung, Mohammad Ryan Pinasthika, Muhammad Azka Obila Vasya, Rania Aprilia Dwi Setya Putri, Agustinus Parasian Tampubolon, Rakan Fadhil Prayata, Septia Khoirin Nisa, Novanto Yudistira

“…Metode yang digunakan untuk mendeteksi dan mengklasifikasikan potato beetle adalah Convolutional Neural Network (CNN) yang merupakan algoritma jaringan syaraf tiruan yang efektif dalam pengolahan citra. …”
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Prediksi Kesiapan Sekolah Menggunakan Machine Learning Berbasis Kombinasi Adam dan Nesterov Momentum by Indah Mustika Rahayu, Ahmad Yusuf, Mujib Ridwan

“…Penelitian menggunakan algoritma Artificial Neural Network dengan metode optimasi kombinasi Adam dan Nesterov Momentum. …”
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