Construction of Value Chain E-Commerce Model Based on Stationary Wavelet Domain Deep Residual Convolutional Neural Network by Chenyuan Wang

“…The original loss function based on the residual learning model deep learning is modified to solve the original model fuzzy problem, which improves the effect and has good robustness. …”
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Offline English Handwritten Character Recognition using Sequential Convolutional Neural Network by Muhammad Iqbal, Muniba Humayun, Raheel Siddiqi, Christopher J. Harrison, Muneeb Abid Malik

“…The main idea of this research paper is to propose a deep learning CNN method to help recognize English characters. …”
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Stock price prediction with attentive temporal convolution-based generative adversarial network by Ying Liu, Xiaohua Huang, Liwei Xiong, Ruyu Chang, Wenjing Wang, Long Chen

“…Furthermore, when compared to the deep learning method GRU, ACTGAN reduced the Mean Absolute Error (MAE) by 51.01%. …”
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Sistem Isyarat Bahasa Indonesia (SIBI) Metode Convolutional Neural Network Sequential secara Real Time by Oky Dwi Nurhayati, Dania Eridani, Muhammad Hafiz Tsalavin

“…Perangkat tambahan yang dikembangkan dalam penelitian ini melibatkan teknologi visi komputer deep learning sehingga menghasilkan tools untuk menerjemahkan bahasa isyarat tangan. …”
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Similarity-Based Summarization of Music Files for Support Vector Machines by Jan Jakubik, Halina Kwaśnicka

“…Recent advancements in the area rely on the use of deep learning, which allows researchers to operate on a low-level description of the music. …”
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A large-scale dataset for Chinese historical document recognition and analysis by Yongxin Shi, Dezhi Peng, Yuyi Zhang, Jiahuan Cao, Lianwen Jin

“…Recently, researchers have tried to utilize deep-learning techniques to automate recognition and analysis. …”
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Enhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions. by Lingbo Li, Runpu Wang, Miaojie Zou, Fusen Guo, Yuheng Ren

“…However, existing deep learning-based garbage image classification models generally suffer from low classification accuracy, insufficient robustness, and slow detection speed due to the large number of model parameters. …”
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IQNet: Image Quality Assessment Guided Just Noticeable Difference Prefiltering for Versatile Video Coding by Yu-Han Sun, Chiang Lo-Hsuan Lee, Tian-Sheuan Chang

“…Our method demonstrates higher perceptual quality and a model size that is an order of magnitude smaller than previous deep learning methods.…”
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A lightweight power quality disturbance recognition model based on CNN and Transformer by ZHANG Bide, QIU Jie, LOU Guangxin, ZHOU Can, LUO Qingqing, LI Tianqian

“…Its lightweight, end-to-end design also results in shorter inference times compared to other deep learning models.…”
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Enhancing Classification Models With Sophisticated Counterfactual Images by Xiang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

“…In deep learning, training data, which are mainly from realistic scenarios, often carry certain biases. …”
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Data-Driven Approach for Modeling the Nonlane-Based Mixed Traffic Conditions by Narayana Raju, Shriniwas S. Arkatkar, Said Easa, Gaurang Joshi

“…The results show that a deep learning model and k-NN tend to replicate better-mixed traffic conditions than random forest and regression trees.…”
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Causality-driven candidate identification for reliable DNA methylation biomarker discovery by Xinlu Tang, Rui Guo, Zhanfeng Mo, Wenli Fu, Xiaohua Qian

“…Overall, this study offers a causal-deep-learning-based perspective with a compatible tool to identify reliable DNAm biomarker candidates, promoting resource-efficient biomarker discovery.…”
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A Time-Aware CNN-Based Personalized Recommender System by Dan Yang, Jing Zhang, Sifeng Wang, XueDong Zhang

“…With the in-depth study and application of deep learning algorithms, deep neural network is gradually used in recommender systems. …”
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Kontrol Level Kecepatan Kipas Melalui Deteksi Gestur Jari Tangan Menggunakan MediaPipe dan Faster-RCNN by Muhammad Aldi Fakhruddin, Heri Pratikno, Musayyanah, Weny Indah Kusumawati

“…Mikrokontroler yang digunakan pada penelitian ini adalah Arduino Uno, sedangkan penerapan computer vision for deep learning menggunakan framework MediaPipe dan Faster-RCNN. …”
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NuFold: end-to-end approach for RNA tertiary structure prediction with flexible nucleobase center representation by Yuki Kagaya, Zicong Zhang, Nabil Ibtehaz, Xiao Wang, Tsukasa Nakamura, Pranav Deep Punuru, Daisuke Kihara

“…To address this challenge, we developed NuFold, a novel computational approach that leverages state-of-the-art deep learning architecture to accurately predict RNA tertiary structures. …”
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Optimized digital workflow for pathologist-grade evaluation in bleomycin-induced pulmonary fibrosis mouse model by Toshiki Goto, Akira Sano, Shinichi Onishi, Natsuko Hada, Rui Kimata, Saori Matsuo, Sohei Oyama, Atsuhiko Kato, Hideaki Mizuno, Masaki Yamazaki

“…Therefore, we developed a new workflow for BLM model that reduces inter- and intra-observer variations and improves the evaluation process. We generated deep learning models for grading lung fibrosis that were able to achieve accuracy comparable to that of pathologists. …”
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A Joint Deep Recommendation Framework for Location-Based Social Networks by Omer Tal, Yang Liu

“…In addition, we provide further insight into the design selections and hyperparameters of our recommender system, hoping to shed light on the benefit of deep learning for location-based social network recommendation.…”
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Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images by Avigyan Roy, Priyam Saha, Nandita Gautam, Friedhelm Schwenker, Ram Sarkar

“…Convolutional neural network based pretrained deep learning models can be used successfully to detect lung cancer. …”
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Research on the improvement method of imbalance of ground penetrating radar image data by Ligang Cao, Lei Liu, Congde Lu, Ruimin Chen

“…This leads to poor accuracy of deep learning for injury classification. And the cost of collecting a large amount of data in the field is higher. …”
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Predicting and synthesizing terahertz spoof surface plasmon polariton devices with a convolutional neural network model by Vahid Najafy, Bijan Abbasi-Arand, Maryam Hesari-Shermeh

“…Abstract With the increasing global attention to deep learning and the advancements made in applying convolutional neural networks in electromagnetics, we have recently witnessed the utilization of deep learning-based networks for predicting the spectrum and electromagnetic properties of structures instead of traditional tools like fully numerical-based methods. …”
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