Comparison of discrete transforms for deep‐neural‐networks‐based speech enhancement by Wissam A. Jassim, Naomi Harte

“…In addition to the DFT, seven different transforms were tested: discrete Cosine transform, discrete Sine transform, discrete Haar transform, discrete Hadamard transform, discrete Tchebichef transform, discrete Krawtchouk transform, and discrete Tchebichef‐Krawtchouk transform. …”
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AquaYOLO: Advanced YOLO-based fish detection for optimized aquaculture pond monitoring by M. Vijayalakshmi, A. Sasithradevi

“…Fish detection is a key challenging step in these vision-based systems, as it faces challenges such as changing light conditions, varying water clarity, different types of vegetation, and dynamic backgrounds. …”
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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

“…This paper provides a comprehensive overview of various machine learning algorithms applied across different subfields of astrophysics, elucidating their applications, advantages, and the challenges they address. …”
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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

“…The GCN module is responsible for extracting spatial features from the skeletal graph, while the SNN module evaluates the similarity between different skeletal sequences by comparing their features. …”
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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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A Deep Learning Strategy for the Retrieval of Sea Wave Spectra from Marine Radar Data by Giovanni Ludeno, Giuseppe Esposito, Claudio Lugni, Francesco Soldovieri, Gianluca Gennarelli

“…The results demonstrate that the proposed approach is effective in reconstructing the directional wave spectrum across different sea states.…”
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An Improved Deep Learning Model for Online Tool Condition Monitoring Using Output Power Signals by Lang Dai, Tianyu Liu, Zhongyong Liu, Lisa Jackson, Paul Goodall, Changqing Shen, Lei Mao

“…Furthermore, with test data collected at cutting tools with different sizes, the robustness of the proposed method can be further clarified.…”
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Conflict between genetic and phenotypic differentiation: the evolutionary history of a 'lost and rediscovered' shorebird. by Frank E Rheindt, Tamás Székely, Scott V Edwards, Patricia L M Lee, Terry Burke, Peter R Kennerley, David N Bakewell, Monif Alrashidi, András Kosztolányi, Michael A Weston, Wei-Ting Liu, Wei-Pan Lei, Yoshimitsu Shigeta, Sálim Javed, Sama Zefania, Clemens Küpper

“…Alternatively, gene expression differences may be crucial in producing different phenotypes whereas neutral differentiation may be lagging behind.…”
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Analysis of Single-Pilot Intention Modeling in Commercial Aviation by Lei Dong, Hongbing Chen, Changxiao Zhao, Peng Wang

“…This was done to avoid safety hazards caused by different intents and inconsistent operations of the single pilot and the cockpit automation system. …”
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GaitRGA: Gait Recognition Based on Relation-Aware Global Attention by Jinhang Liu, Yunfan Ke, Ting Zhou, Yan Qiu, Chunzhi Wang

“…The major challenges in gait recognition include changes in viewing angle, occlusion, clothing changes, and significant differences in gait characteristics under different walking conditions. …”
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Influence of cognitive networks and task performance on fMRI-based state classification using DNN models by Murat Kucukosmanoglu, Javier O. Garcia, Justin Brooks, Kanika Bansal

“…Here, we employ two different and complementary DNN models, a one-dimensional convolutional neural network (1D-CNN) and a bidirectional long short-term memory network (BiLSTM), to classify cognitive task states from fMRI data, focusing on the cognitive underpinnings of the classification. …”
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AI-Assisted identification of sex-specific patterns in diabetic retinopathy using retinal fundus images. by Parsa Delavari, Gulcenur Ozturan, Eduardo V Navajas, Ozgur Yilmaz, Ipek Oruc

“…Here we examine whether DR manifests differently in male and female patients, using a dataset of retinal images and leveraging convolutional neural networks (CNN) integrated with explainable artificial intelligence (AI) techniques. …”
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Multi-anchor adaptive fusion and bi-focus attention for enhanced gait-based emotion recognition by Jincheng Li, Xuejing Dai, Ruiao Yan, Chengqing Tang, Yunpeng Li

“…The MAAF module captures multi-scale temporal features to understand emotional expressions across different time ranges, while the BFA module focuses on both local and global features, enhancing the model’s ability to capture complex emotional information. …”
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A Novel Approach for Identifying and Eliminating the Degradations in Real Time Images by S. Rajkumar, L. M. Jenila Livingston, Vansh Juneja, Shashwat Sharv, Pratik Dattatray Mahajan

“…The CNN model is trained on a dataset of images with various noises, learning to discriminate between different noise patterns. After classifying the type of noise, we apply a enhancement approach utilizes deep learning techniques by leveraging U-Net based CNN model to reduce noise levels in an image. …”
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Systematic Review on Automation of Central Tire Inflation System Based on Terrain Conditions by Carl Luis C. Ledesma, Charlothe John I. Tablizo, Marites B. Tabanao, Emmanuel A. Salcedo, Emmy Grace T. Requillo, John Paul T. Cruz

“…Incorrect vehicle tire pressure affects vehicle dynamics, fuel efficiency, and driver safety across different terrain conditions. The current central tire inflation system (CTIS) alleviates this issue by adjusting the tire pressure to a predetermined reference level. …”
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End-to-End Intelligent Fault Diagnosis of Transmission Bearings in Electric Vehicles Based on CNN by Yong Chen, Guangxin Li, Anhe Li, Bolin He

“…The original time-domain vibration signal numerical matrix of the bearing is trained and tested to extract and learn abstract fault features of different fault types, and then the fault classification of the bearing is achieved. …”
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GNSS–VTEC prediction based on CNN–GRU neural network model during high solar activities by T. Y. Yang, J. Y. Lu, Y. Y. Yang, Y. H. Hao, M. Wang, J. Y. Li, G. C. Wei

“…Furthermore, the CNN–GRU model exhibits stable and excellent performance across different months and hour of the day, even during geomagnetic storms.…”
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