EEG Depression Recognition Based on Multi-domain Features Combined with CBAM Model by CHEN Yu, HU Xiuxiu, WANG Sheng

“…Firstly, the continuous wavelet transform (CWT) is used to extract time-frequency domain features, and combined with the spatial information of EEG electrodes to form a 2D feature image, which jointly retains the spatial, time and frequency information of EEG; then the convolutional neural network (CNN) is used) to extract spatial and frequency domain features, and then input bidirectional long and short-term memory ( BiLSTM) to capture time information; finally combined with attention mechanism (AM) , different weights are assigned to the multi-domain features extracted from the network, enabling the selection of more representative depressive features, thereby improving the accuracy of identifying depression. …”
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Single-level Discrete Two Dimensional Wavelet Transform Based Multiscale Deep Learning Framework for Two-Wheeler Helmet Detection by Amrutha Annadurai, Manas Ranjan Prusty, Trilok Nath Pandey, Subhra Rani Patra

“…METHODS: The proposed helmet classification approach utilizes the Multi-Scale Deep Convolutional Neural Network (CNN) framework cascaded with Long Short-Term Memory (LSTM) network. …”
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Multimodal fusion based few-shot network intrusion detection system by Congyuan Xu, Yong Zhan, Zhiqiang Wang, Jun Yang

“…Existing few-shot learning methods, while reducing reliance on large datasets, mostly handle single-modality data and fail to fully exploit complementary information across different modalities, limiting detection performance. …”
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Artificial Intelligence for Earthquake Prediction: A Preliminary System Based on Periodically Trained Neural Networks Using Ionospheric Anomalies by Sergio Baselga

“…The use of three-dimensional data matrices, having spatiotemporal information to feed a convolutional neural network, is proposed in this contribution. …”
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RETRACTED PAPER: Enhancing 3D human pose estimation through multi-feature fusion by Xianlei GE, Vladimir MARIANO

“…The proposed model utilizes convolutional kernels of different sizes to extract feature maps with diverse resolutions and dimensions. …”
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Brain Representation in Conscious and Unconscious Vision by Ning Mei, David Soto

“…Here we re-analysed data from a high-precision fMRI study coupled with representational similarity analysis based on convolutional neural network models to provide a detailed information-based approach to neural representations of both unconscious and conscious perceptual content. …”
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UMEDNet: a multimodal approach for emotion detection in the Urdu language by Adil Majeed, Hasan Mujtaba

“…In the end, we analyzed the impact of UMEDNet and found that our model integrates data on different modalities and leads to better performance.…”
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Intelligent Model for Brain Tumor Identification Using Deep Learning by Abdul Hannan Khan, Sagheer Abbas, Muhammad Adnan Khan, Umer Farooq, Wasim Ahmad Khan, Shahan Yamin Siddiqui, Aiesha Ahmad

“…The processing of medical images plays a crucial role in assisting humans in identifying different diseases. The classification of brain tumors is a significant part that depends on the expertise and knowledge of the physician. …”
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Multiple sclerosis diagnosis with brain MRI retrieval: A deep learning approach by R.M. Haggag, Eman M. Ali, M.E. Khalifa, Mohamed Taha

“…We experiment with Nine different distance metrics to measure query and database image similarity. …”
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Ambiguous facial expression detection for Autism Screening using enhanced YOLOv7-tiny model by Akhil Kumar, Ambrish Kumar, Dushantha Nalin K. Jayakody

“…Children with autism spectrum disorder show ambiguous facial expressions which are different from the facial attributes of normal children. …”
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Development of Ai-Based Crop Quality Grading Systems using Image Recognition by Dusi Prerna, Sharma Pooja

“…It also integrate Convolutional Neural Networks (CNN), Transfer Learning, Support Vector Machines (SVM) and Random Forest algorithms to label crop images into pre defined categories. …”
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Comparison of discrete transforms for deep‐neural‐networks‐based speech enhancement by Wissam A. Jassim, Naomi Harte

“…Two deep‐learning architectures were tested: convolutional neural networks (CNN) and fully connected neural networks. …”
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AquaYOLO: Advanced YOLO-based fish detection for optimized aquaculture pond monitoring by M. Vijayalakshmi, A. Sasithradevi

“…The backbone of AquaYOLO employs CSP layers and enhanced convolutional operations to extract hierarchical features. …”
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The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports. by Guomei Cui, Chuanjun Wang

“…Specifically, by introducing adaptive feature selection and ensemble learning methods, the decision tree algorithm effectively improves the recognition ability of the model for different athletes and sports states, thus reducing the over-fitting phenomenon and improving the generalization ability. …”
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Deep Learning Classification of Simulated Surface EMG Signals across Maximum Voluntary Contraction Levels by Radhouane Hammach, Samia Belkacem, Noureddine Messaoudi, Raïs El’hadi Bekka

“…Due to the complex nature of EMG signals, different approaches, based on artificial intelligence and machine learning, were developed for EMG signal analysis and NMD diagnosis. …”
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University proceedings. Volga region. Technical sciences by V.I. Volchikhin, A.I. Ivanov, P.E. Selivanov, E.A. Malygina

“…Currently, multilayer convolutional networks of artificial deep learning neurons are actively used to recognize people's faces. …”

Deep Space Insights: Machine Learning Revolutionizing Astrophysical Discoveries by Dutta Samya, Paul Prithwineel

“…Convolutional Neural Networks are essential for visual data analysis, helping in galaxy classification and exoplanet transit detection. …”
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The use of artificial intelligence-based Siamese neural network in personalized guidance for sports dance teaching by Yi Xie, Yao Yan, Yuwei Li

“…First, a human skeletal graph is constructed. A graph convolutional network (GCN) is employed to extract features from the nodes (joints) and edges (bone connections) in the graph structure, capturing both spatial relationships and temporal dynamics between joints. …”
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Real-time playing technique recognition embedded in a smart acoustic guitar by Domenico Stefani, Luca Turchet

“…The recognition pipeline includes an onset detector, feature extractors, and a convolutional neural classifier. Four pipeline configurations are proposed, striking different balances between accuracy and sound-to-result latency. …”
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AI approaches for phenotyping Alzheimer's disease and related dementias using electronic health records by Sara Knox, Stephanie Aghamoosa, Paul M. Heider, Maxwell Cutty, Andrew Wright, Dmitry Scherbakov, Gabriel Hood, Sara A. Nolin, Jihad S. Obeid

“…RESULTS A foundational LLM derived from Llama 2 demonstrated superior performance in identifying patients with ADRD (area under the curve [AUC] = 0.9534, F1 score 0.8571) compared to both the current standard CCW algorithm (AUC = 0.8482, F1 score 0.8323, although only the AUC was statistically significantly different) and other AI‐based models. Several of the AI‐based models, including convolutional neural networks, also outperformed the CCW algorithm. …”
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