The Importance of Urban Transportation, Managements and Strategies for Sustainable City by Süleyman Ay

“…This article is about current problems in urban transportation planning and new developments. …”
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Deep Learning-Based Music Quality Analysis Model by Jing Jing

“…First, a variety of task classifications for the music signal problem are divided. Afterward, the optimization and adoption of deep learning in the two major problems of music feature extraction and sequence modeling are introduced. …”
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An ensemble approach using multidimensional convolutional neural networks in wavelet domain for schizophrenia classification from sMRI data by Tamilarasi Sarveswaran, Vijayarajan Rajangam

“…Abstract Schizophrenia is a complicated mental condition marked by disruptions in thought processes, perceptions, and emotional responses, which can cause severe impairment in everyday functioning. sMRI is a non-invasive neuroimaging technology that visualizes the brain’s structure while providing precise information on its anatomy and potential problems. This paper investigates the role of multidimensional Convolutional Neural Network (CNN) architectures: 1D-CNN, 2D-CNN and 3D-CNN, using the DWT subbands of sMRI data. 1D-CNN involves energy features extracted from the CD subband of sMRI data. …”
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Improving the navigation optimization of hospital logistics robots under complex lighting changes by using improved ORB-SLAM3 and deep learning visual SLAM algorithm by Feng Xiao, Youhai Zhang, Jie Fang, Xing Guo, Rubing Huang

“…Abstract Under complex lighting conditions, hospital logistics robots are facing serious challenges in positioning and navigation.The traditional ORB (Oriented FAST and rotated BRIEF) algorithm often has problems such as unstable feature point extraction, poor positioning accuracy, and long navigation path planning time in environments with large lighting changes, which greatly affects the robot's navigation efficiency and accuracy. …”
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Polska produkcja filmowa po roku 2005 w perspektywie badań ilościowych by Anna Wróblewska

“…The number of Polish feature films increased from 20-25 in2000-2005 to 40-55 in2007-2011.  …”
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Deep factorization machine model based on attention capsule by Yiran GU, Zhupeng YAO, Haigen YANG

“…Aiming at the problems of single feature combination of recommendation model, resolution of a large amount of valuable feature information, and over-fitting in deep learning, a new attentional scoring mechanism called attention capsule was designed, and a deep factorization machine model based on attention capsule was proposed.Users’ historical clicking and candidate items were processed through weight calculation based on the DeepFM model, reducing the impact of irrelevant features on the model, and the differential impact of different historical behaviors on users’ interests was fully explored.The adaptive regularization formulation was added to the training, which effectively reduced over-fitting without affecting the training speed.The comparison test on two public data sets shows that the proposed model is significantly enhanced in loss function and GAUC compared to other models.…”
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Optical fiber eavesdropping detection method based on machine learning by Xiaolian CHEN, Yi QIN, Jie ZHANG, Yajie LI, Haokun SONG, Huibin ZHANG

“…Optical fiber eavesdropping is one of the major hidden dangers of power grid information security,but detection is difficult due to its high concealment.Aiming at the eavesdropping problems faced by communication networks,an optical fiber eavesdropping detection method based on machine learning was proposed.Firstly,seven-dimensions feature vector extraction method was designed based on the influence of eavesdropping on the physical layer of transmission.Then eavesdropping was simulated and experimental feature vectors were collected.Finally,two machine learning algorithms were used for classification detection and model optimization.Experiments show that the performance of the neural network classification is better than the K-nearest neighbor classification,and it can achieve 98.1% eavesdropping recognition rate in 10% splitting ratio eavesdropping.…”
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Lip Print Recognition Algorithm Based on Convolutional Network by Hongcheng Zhou

“…In order to solve the complex image preprocessing problems, difficult feature extraction by artificial design algorithm, and low accuracy of lip print recognition, a method based on the convolutional neural network is proposed, by building a convolutional neural network called LPRNet (Lip Print Recognition Network). …”
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Deep factorization machine model based on attention capsule by Yiran GU, Zhupeng YAO, Haigen YANG

“…Aiming at the problems of single feature combination of recommendation model, resolution of a large amount of valuable feature information, and over-fitting in deep learning, a new attentional scoring mechanism called attention capsule was designed, and a deep factorization machine model based on attention capsule was proposed.Users’ historical clicking and candidate items were processed through weight calculation based on the DeepFM model, reducing the impact of irrelevant features on the model, and the differential impact of different historical behaviors on users’ interests was fully explored.The adaptive regularization formulation was added to the training, which effectively reduced over-fitting without affecting the training speed.The comparison test on two public data sets shows that the proposed model is significantly enhanced in loss function and GAUC compared to other models.…”
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Improving Performance Of Hmm-based Asr For Gsm-efr Speech Coding by Lallouani Bouchakour, Mohamed Debyeche

“…Specifically, we suggest extracting the recognition feature vectors directly from the encoded speech bit-stream instead of decoding it and subsequently extracting the feature vectors. …”
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A New Strategy for the Approximate Solution of Hyperbolic Telegraph Equations in Nonlinear Vibration System by Jiao Zeng, Asma Idrees, Mohammed S. Abdo

“…The most significant feature of this approach is that we do not require any restriction of variables and hypotheses to find the results of nonlinear problems. …”
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Complex dark environment-oriented object detection method based on YOLO-AS by Bin Ren, Zhaohui Xu, Junwu Zhao, Rujiang Hao, Jianchao Zhang

“…Abstract For object detection in complex dark environments, the existing methods generally have problems such as low detection accuracy, false detection and missed detection. …”
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Wind Power Prediction considering Ramping Events Based on Generative Adversarial Network by Qiyue Huang

“…Taking the feature set which integrates similar feature with historical one as the input of GAN, the simulated ramping data are continuously produced through the adversarial training of the generator and discriminator, thus enriching the ramping database. …”
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Classification of offshore wind grid-connected power quality disturbances based on fast S-transform and CPO-optimized convolutional neural network. by Minan Tang, Hongjie Wang, Jiandong Qiu, Zhanglong Tao, Tong Yang

“…Then, the CPO-CNN classification model is used for feature extraction and feature selection of the time-frequency diagrams and classification of multiple power quality disturbances. …”
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High resolution remote sensing image object detection algorithm based on improved YOLOv8 by ZHANG Xia, QIAO Huanyu, CAO Feng

“…Attention-based Intra-scale feature interaction was used. Bi-directional feature pyramid network and semantics and detail infusion module were combined as the algorithm's feature fusion network. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…Aiming at the common low accuracy and efficiency problems in underwater target detection, this paper designs an innovative algorithm based on the YOLOv7 framework. …”
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Optimized Negative Selection Algorithm for Image Classification in Multimodal Biometric System by Monsurat Omolara Balogun, Latifat Adeola Odeniyi, Elijah Olusola Omidiora, Stephen Olatunde Olabiyisi, Adeleye Samuel Falohun

“…The ONSA is characterized by the ability to consider whole feature spaces (feature selection balance), having good training capability and low scalability problems. …”
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A Derivative-Free Conjugate Gradient Method and Its Global Convergence for Solving Symmetric Nonlinear Equations by Mohammed Yusuf Waziri, Jamilu Sabi’u

“…This derivative-free feature of the proposed method gives it advantage to solve relatively large-scale problems (500,000 variables) with lower storage requirement compared to some existing methods. …”
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Characteristics Analysis of Mental Health Data of College Students Based on Convolutional Neural Network and TOPSIS Evaluation Model by Lanfeng Zhou

“…With the rapid development of modern society, there are many problems concerning the physical and mental health of students. …”
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Design of a Convolutional Neural Network with Type-2 Fuzzy-Based Pooling for Vehicle Recognition by Cheng-Jian Lin, Bing-Hong Chen, Chun-Hui Lin, Jyun-Yu Jhang

“…Convolutional neural networks typically employ convolutional layers for feature extraction and pooling layers for dimensionality reduction. …”
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