Neuromorphic system using capacitor synapses by Reon Oshio, Takumi Kuwahara, Takeru Aoki, Mutsumi Kimura, Yasuhiko Nakashima

“…Abstract Artificial intelligences are indispensable social infrastructures, neural networks are embodiment methodologies, and neuromorphic systems are promising solutions for compact size and low energy. …”
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Reduced-Order Modeling of Cavity Flow Oscillations across Multi-Mach Numbers Using Deep Learning by Zhe Liu, Fangli Ning, Hui Ding, Qingbo Zhai, Juan Wei

“…Then, two deep learning frameworks, including multilayer perceptron (MLP) and long short-term memory (LSTM) neural networks, are used to predict the future POD coefficients, respectively. …”
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Bioinformatics-driven deep learning for nail disease diagnosis: A novel approach to improve healthcare outcomes by Ardianto Rian, Yusuf Dede, Sumantri Raden Bagus Bambang, Febrina Dina, Al-Hakim Rosyid R., Ariyanto Arif Setia Sandi

“…In order to increase awareness of the importance of nail care in preventing disease and enhancing quality of life, this study investigates the use of convolutional neural networks, or CNNs. Onychomycosis and other nail disorders are quite prevalent worldwide and are associated with inadequate personal cleanliness. …”
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Impact of facial tattoos and paintings on face recognition systems by Mathias Ibsen, Christian Rathgeb, Thomas Fink, Pawel Drozdowski, Christoph Busch

“…Abstract In recent years, face recognition technologies have shown impressive recognition performance, mainly due to recent developments in deep convolutional neural networks. Notwithstanding those improvements, several challenges which affect the performance of face recognition systems remain. …”
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Transient State Estimation for Power System Based on Deep Transfer Learning by JIAO Hao, ZHAO Jiawei, WEI Lei, ZHU Weiping, MA Zhoujun, ZANG Haixiang

“…Simulations demonstrate that the proposed method exhibits a higher estimation accuracy and computational efficiency than that of deep neural networks without transfer learning，particularly during power system failures.…”
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A dataset of blood slide images for AI-based diagnosis of malariaDataverse by Rose Nakasi, Joyce Nakatumba Nabende, Jeremy Francis Tusubira, Aloyzius Lubowa Bamundaga, Alfred Andama

“…The labelled image data can be used to build computational models implemented with convolution neural networks. The dataset has 3000 labelled thick blood smear images and 1000 labelled thin blood smear images. …”
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AI Methods for Antimicrobial Peptides: Progress and Challenges by Carlos A. Brizuela, Gary Liu, Jonathan M. Stokes, Cesar de laFuente‐Nunez

“…Despite significant contributions, existing reviews have not thoroughly explored the potential of large language models (LLMs), graph neural networks (GNNs) and structure‐guided AMP discovery and design. …”
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Machine learning and facial recognition for down syndrome detection: A comprehensive review by Khosro Rezaee

“…This paper explores various facial analysis techniques, including deep convolutional neural networks (DCNNs) and hybrid models combining traditional image processing with deep learning. …”
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In situ real-time measurement for electron spin polarization in atomic spin gyroscopes by Feng Li, Haoying Pang, Zhuo Wang, Wenfeng Fan, Min Zhang, Zehua Liu, Jiahang Li, Bodong Qin, Xinxiu Zhou, Xusheng Lei, Ruigang Wang

“…By utilizing artificial neural networks, we derive an output equation for electron spin polarization, using transmitted laser power and cell temperature as independent variables. …”
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Machine Learning with Variable Sampling Rate for Traffic Prediction in 6G MEC IoT by Rongqun Peng, Xiuhua Fu, Tian Ding

“…We investigate in detail the impact of variable sampling rate on traffic prediction and propose a high-speed traffic prediction method using machine learning and recurrent neural networks. We first investigate a VSR-NLMS adaptive prediction method to perform time series prediction dataset transformation. …”
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Classification of Stages 1,2,3 and Preplus, Plus disease of ROP using MultiCNN_LSTM classifier by Ranjana Agrawal, Sucheta Kulkarni, Madan Deshpande, Anita Gaikwad, Rahee Walambe, Ketan V. Kotecha

“…This is accomplished by using multiple CNNs (Convolutional Neural Networks) to extract features and LSTM (Long Short-Term Memory) classifier to classify images. • Cropped STAGE dataset and HVDROPDB-PLUS dataset are constructed with RetCam and Neo images. • The proposed networks outperform individual CNNs and CNN_LSTM networks in terms of accuracy and F1 score.…”
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Research on multi-source microstructure image recognition of foam ceramics using convolutional network combine with frequency domain by Yi Yin, Jianwei Pan, Fang Wang, Peihang Li, Zhen Cai, Xin Xu

“…To address this, a novel artificial intelligence recognition model, FD-Conv, is proposed, which combines the global information processing capabilities of Transformers with the local feature extraction strengths of convolutional neural networks. Additionally, a frequency domain block detail enhancement mechanism is introduced to improve recognition accuracy. …”
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Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses by Ying Xiong, Linpeng Yao, Jinglai Lin, Jiaxi Yao, Qi Bai, Yuan Huang, Xue Zhang, Risheng Huang, Run Wang, Kang Wang, Yu Qi, Pingyi Zhu, Haoran Wang, Li Liu, Jianjun Zhou, Jianming Guo, Feng Chen, Chenchen Dai, Shuo Wang

“…Two multi-phase convolutional neural networks are developed to predict the malignancy and aggressiveness of renal masses. …”
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Distributed representations enable robust multi-timescale symbolic computation in neuromorphic hardware by Madison Cotteret, Hugh Greatorex, Alpha Renner, Junren Chen, Emre Neftci, Huaqiang Wu, Giacomo Indiveri, Martin Ziegler, Elisabetta Chicca

“…Programming recurrent spiking neural networks (RSNNs) to robustly perform multi-timescale computation remains a difficult challenge. …”
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ResInceptNet-SA: A Network Traffic Intrusion Detection Model Fusing Feature Selection and Balanced Datasets by Guorui Liu, Tianlin Zhang, Hualin Dai, Xinyang Cheng, Daoxuan Yang

“…In this paper, a new type of model (ResIncepNet-SA) based on InceptionNet, Resnet, and convolutional neural networks with a self-attention mechanism was proposed to detect network intrusions. …”
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Investigation of Nonlinear Vibrational Analysis of Circular Sector Oscillator by Using Cascade Learning by Naveed Ahmad Khan, Muhammad Sulaiman, Jamel Seidu, Fahad Sameer Alshammari

“…Furthermore, a computational strength of Cascade neural networks (CNNs) is utilized with backpropagated Levenberg–Marquardt (BLM) algorithm to study the oscillations in angular displacement θ, velocity θ′, and acceleration θ″. …”
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Neuro-Fuzzy Model for the Prediction and Classification of the Fused Zone Levels of Imperfections in Ti6Al4V Alloy Butt Weld by Giuseppe Casalino, Sabina Luisa Campanelli, Fabrizio Memola Capece Minutolo

“…Weld imperfections were connected to the welding parameters by feed forward neural networks. Then the imperfections were clustered using the C-means fuzzy clustering algorithm. …”
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Non-linear multi-objective optimization model of production planning based on fuzzy logic and machine learning by Zahra Saeidi Mobarakeh, Hossein Amoozadkhalili

“…This fuzzy logic is combined with machine learning algorithms such as neural networks and reinforcement learning to create an intelligent and flexible model that effectively adapts to sudden changes in dynamic environments. …”
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Rapid Determination of the Freshness of Lotus Seeds Using Surface Desorption Atmospheric Pressure Chemical Ionization-Mass Spectrometry with Multivariate Analyses by Yunyang Chi, Liping Luo, Xueyong Huang, Meng Cui, Ximo Dai, Yingbin Hao, Xiali Guo, Huolin Luo

“…The obtained data were processed by principal component analysis (PCA) and backpropagation artificial neural networks (BP-ANNs). The result showed that DAPCI-MS could obtain abundant chemical material information from the slice surface of lotus seeds. …”
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On the Potential of Algorithm Fusion for Demographic Bias Mitigation in Face Recognition by Jascha Kolberg, Yannik Schäfer, Christian Rathgeb, Christoph Busch

“…With the rise of deep neural networks, the performance of biometric systems has increased tremendously. …”
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