An Improved Method for Human Activity Detection with High-Resolution Images by Fusing Pooling Enhancement and Multi-Task Learning by Haoji Li, Shilong Ren, Lei Fang, Jinyue Chen, Xinfeng Wang, Guoqiang Wang, Qingzhu Zhang, Qiao Wang

“…Deep learning has garnered increasing attention in human activity detection due to its advantages, such as not relying on expert knowledge and automatic feature extraction. …”
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Barlow Twins deep neural network for advanced 1D drug–target interaction prediction by Maximilian G. Schuh, Davide Boldini, Annkathrin I. Bohne, Stephan A. Sieber

“…By reducing time and cost, machine learning and deep learning can accelerate this laborious discovery process. …”
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Film Recommender System Menggunakan Metode Neural Collaborative Filtering by Ni’mah Khoiriyah Ayyiyah, Retno Kusumaningrum, Rismiyati Rismiyati

“…Penelitian ini menggunakan pendekatan prediksi Collaborative Filtering dengan mengimplementasikan deep learning berdasarkan teknologi Neural Collaborative Filtering pada dataset MovieLens. …”
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PREDICTING USD/ TL EXCHANGE RATE IN TURKEY: THE LONG-SHORT TERM MEMORY APPROACH by Abdul-razak Bawa Yussif, Fatih Mangır, Zeynep Karaçor, Ayten Yağmur

“…In order to perform a more accurate exchange rate prediction, deep-learning methods have been employed withremarkable rates of success. …”
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Image experience prediction for historic districts using a CNN-transformer fusion model by Youping Teng, Weijia Wang

“…The results highlight the practical potential of deep learning in visual sentiment analysis and emphasize the importance of emotional value in improving experiences in historic districts. …”
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Lie Detection Technology of Bimodal Feature Fusion Based on Domain Adversarial Neural Networks by Yan Zhou, Feng Bu

“…First, a deep learning neural network was used as a feature extractor to isolate speech and facial expression features exhibited by the liars. …”
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Drug discovery and mechanism prediction with explainable graph neural networks by Conghao Wang, Gaurav Asok Kumar, Jagath C. Rajapakse

“…The unprecedented development of machine learning and deep learning algorithms has expedited the drug response prediction research. …”
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Modulation recognition driven by signal enhancement by CHENG Fengyun, ZHOU Jin

“…The existing modulation recognition algorithms based on deep learning theory require a large number of IQ signal samples during the training phase. …”
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Efficient Lane Detection Technique Based on Lightweight Attention Deep Neural Network by Zhiting Yao, Xiyuan Chen

“…For self-driving vehicles, detecting lane lines in changeable scenarios is a fundamental yet challenging task. The rise of deep learning in recent years has contributed to the thriving of autonomous driving. …”
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Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI by Sihwan Kim, Changmin Park, Gwanghyeon Jeon, Seohee Kim, Jong Hyo Kim

“…Recent advancements in deep learning have significantly improved medical image segmentation. …”
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Learning by making – student-made models and creative projects for medical education: systematic review with qualitative synthesis by Tan Yong Yi, Panwar Shreyans, Ranganath Vallabhajosyula

“…Creative projects facilitated deep learning objectives via interdisciplinary learning and promoted new ways of perceiving concepts. …”
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The global research of magnetic resonance imaging in Alzheimer’s disease: a bibliometric analysis from 2004 to 2023 by Xiaoyu Sun, Xiaoyu Sun, Jianghua Zhu, Jianghua Zhu, Ruowei Li, Ruowei Li, Yun Peng, Yun Peng, Lianggeng Gong, Lianggeng Gong

“…The current research hotspot is deep learning, which is being applied to develop noninvasive diagnosis and safer treatment of AD.…”
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Penerapan Deep Convolutional Generative Adversarial Network Untuk Menciptakan Data Sintesis Perilaku Pengemudi Dalam Berkendara by Michael Stephen Lui, Fitra Abdurrachman Bachtiar, Novanto Yudistira

“…Penggunaan sensor visual memiliki performa yang lebih baik ketika menggunakan metode deep learning. Salah satu metode untuk meningkatkan performa metode deep learning adalah dengan menggunakan data sintesis hasil model generatif sebagai tambahan data. …”
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Image forgery detection algorithm based on U-shaped detection network by Zhuzhu WANG

“…Aiming at the defects of traditional image tampering detection algorithm relying on single image attribute,low applicability and current high time-complexity detection algorithm based on deep learning,an U-shaped detection network image forgery detection algorithm was proposed.Firstly,the multi-stage feature information in the image by using the continuous convolution layers and the max-pooling layers was extracted by U-shaped detection network,and then the obtained feature information to the resolution of the input image through the upsampling operation was restored.At the same time,in order to ensure higher detection accuracy while extracting high-level semantic information of the image,the output features of each stage in U-shaped detection network would be merged with the corresponding output features through the upsampling layer.Further the hidden feature information between tampered and un-tampered regions in the image upon the characteristics of the general network was explored by U-shaped detection network,which could be realized quickly by using its end-to-end network structure and extracting the attributes of strong correlation information among image contexts that could ensure high-precision detection results.Finally,the conditional random field was used to optimize the output of the U-shaped detection network to obtain a more exact detection results.The experimental results show that the proposed algorithm outperforms those traditional forgery detection algorithms based on single image attribute and the current deep learning-based detection algorithm,and has good robustness.…”
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Multisegment Mapping Network for Massive MIMO Detection by Yongzhi Yu, Jianming Wang, Limin Guo

“…However, the use of deep learning for massive MIMO detection can achieve a high degree of computational parallelism, and deep learning constitutes an important technical approach for solving the signal detection problem. …”
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Efficient Data Augmentation Methods for Crop Disease Recognition in Sustainable Environmental Systems by Saebom Lee, Sokjoon Lee

“…Geometric transformations and color space augmentation techniques are applied to validate the efficiency of deep learning models, specifically convolution and transformer models, in recognizing multiple crop diseases. …”
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Predicted Anchor Region Proposal with Balanced Feature Pyramid for License Plate Detection in Traffic Scene Images by Hoanh Nguyen

“…License plate detection is a key problem in intelligent transportation systems. Recently, many deep learning-based networks have been proposed and achieved incredible success in general object detection, such as faster R-CNN, SSD, and R-FCN. …”
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Klasifikasi Aktivitas Manusia Menggunakan Metode Long Short-Term Memory by Latansa Nurry Izza Afida, Fitra Abdurrachman Bachtiar, Imam Cholissodin

“…Sehingga pada penelitian ini menerapkan dataset primer dengan menggunakan label kelas sebanyak 16 sehingga diusulkan metode deep learning Long Short Term Memory (LSTM). Proses penelitian dimulai dari pengambilan data, preprocessing data, modelling dan perbandingan algoritma deep learning LSTM dan machine learning KNN. …”
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Performance Improvement with Reduced Number of Channels in Motor Imagery BCI System by Ali Özkahraman, Tamer Ölmez, Zümray Dokur

“…The study uses advanced deep learning techniques, including multiple 1D convolution blocks and depthwise-separable convolutions, to optimize classification accuracy. …”
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Compensating CBCT Motion Artifacts with Any 2D Generative Model by Yipeng Sun, Linda-Sophie Schneider, Mingxuan Gu, Siyuan Mei, Siming Bayer, Andreas K. Maier

“…Leveraging two-dimensional (2D) generative models while ensuring consistency between adjacent CBCT slices, our method addresses the limitations of traditional deep learning approaches that process each 2D slice of a three-dimensional (3D) volume independently. …”
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