Research on the Application of Deep Learning Methods in the Field of Image Classification by Peng Yuhui

“…In this paper, it is concluded that these models have achieved high accuracy in fruit classification and the textile field, especially the combination of CNN, RNN and LSTM deep learning methods for feature fusion can enhance the accuracy and robustness of the model. …”
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Aortic Aneurysm Inflammatory Cell Detection with Deep Learning methods by Kristóf-Gergö Nagy, Csaba Szferle, Attila Fintha

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A review of deep learning methods in aquatic animal husbandry by Marzuraikah Mohd Stofa, Fatimah Az Zahra Azizan, Mohd Asyraf Zulkifley

“…Yet, for an automation system to be effectively deployed, it needs an intelligent decision-making system, which is where deep learning techniques come into play. In this article, an extensive methodological review of machine learning methods, primarily the deep learning methods used in aquatic animal husbandry are concisely summarized. …”
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Deep Learning Methods and UAV Technologies for Crop Disease Detection by S. G. Mudarisov, I. R. Miftakhov

“…(Research purpose) The study aims to review and systemize scientific literature on the application of unmanned aerial vehicles, remote sensing technologies and deep learning 24 methods for the early detection and prediction of crop diseases. …”
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Status and challenges of UAV recognition methods based on deep learning by LI Qiqin, YANG Ming, REN Haotian, CHANG Haoliang, ZHANG Xiaoqiang, ZHU Xinyu

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An attack detection method based on deep learning for internet of things by Yihan Yu, Yu Fu, Taotao Liu, Kun Wang, Yishuai An

“…To address these issues, this paper proposes an attack detection method based on deep learning for IoT. Firstly, a genetic algorithm is used for feature selection; secondly, a cost-sensitive function is employed to address the scarcity of attack traffic in IoT; and finally, a combination of Convolutional Neural Networks and Long Short Term Memory Network is utilized to extract spatiotemporal information from the network. …”
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Deep learning Chinese input method with incremental vocabulary selection by Huajian REN, Xiulan HAO, Wenjing XU

“…The core task of an input method is to convert the keystroke sequences typed by users into Chinese character sequences.Input methods applying deep learning methods have advantages in learning long-range dependencies and solving data sparsity problems.However, the existing methods still have two shortcomings: the separation structure of pinyin slicing in conversion leads to error propagation, and the model is complicated to meet the demand for real-time performance of the input method.A deep-learning input method model incorporating incremental word selection methods was proposed to address these shortcomings.Various softmax optimization methods were compared.Experiments on People’s Daily data and Chinese Wikipedia data show that the model improves the conversion accuracy by 15% compared with the current state-of-the-art model, and the incremental vocabulary selection method makes the model 130 times faster without losing conversion accuracy.…”
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Evaluating the method reproducibility of deep learning models in biodiversity research by Waqas Ahmed, Vamsi Krishna Kommineni, Birgitta König-Ries, Jitendra Gaikwad, Luiz Gadelha, Sheeba Samuel

“…This study investigates the reproducibility of deep learning (DL) methods within the biodiversity research. …”
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Deep Exponential Moving Average Learning Method for Sequential Recommendation by WEN Wen, HU Zhixin, HAO Zhifeng

“…To solve these two problems, this paper proposes a deep exponential moving average based learning method for sequential recommendation (DeepEMA). …”
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A Method for Detecting Tomato Maturity Based on Deep Learning by Song Wang, Jianxia Xiang, Daqing Chen, Cong Zhang

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Image Target Detection and Recognition Method Using Deep Learning by Hongyan Sun

“…Based on the analysis of the existing theories of deep learning detection and recognition, this paper summarized the composition and working principle of the traditional image target detection and recognition system and compared the basic models of target detection and recognition, such as R-CNN network, Fast-RCNN network, and Faster-RCNN network. …”
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An advanced deep learning method for pepper diseases and pests detection by Xuewei Wang, Jun Liu, Qian Chen

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A Hybrid GARCH and Deep Learning Method for Volatility Prediction by Hailabe T. Araya, Jane Aduda, Tesfahun Berhane

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Method of accelerating deep learning with optimized distributed cache in containers by Kai ZHANG, Yang CHE

“…When using GPU to train deep learning models with large-scale dataset, the data loading and preprocessing stages often decrease overall performance notably.Lots of GPU computing resources are wasted on waiting for loading data from remote storage.Firstly, the methods of accelerating deep learning training with container and distributed cache were introduced.The architecture and initial optimization of such training system, which was implemented with Alluxio and Kubernetes, were introduced as well.Secondly, the task and data co-located scheduling (TDCS) and the colocated scheduling policy were elaborated.Thirdly, TDCS was implemented in Kubernetes cluster, which made the acceleration result more extensible.Finally, the result of training ResNet50 image classification model on 128 NVIDIAV100 GPU devices demonstrates that the proposed methods can bring 2 to 3 times speed up comparing with load data from remote storage directly.…”
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Helium Speech Recognition Method Based on Spectrogram with Deep Learning by Yonghong Chen, Shibing Zhang, Dongmei Li

“…This study introduces deep learning into helium speech recognition and proposes a spectrogram-based dual-model helium speech recognition method. …”
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Research on Apple Recognition and Localization Method Based on Deep Learning by Zhipeng Zhao, Chengkai Yin, Ziliang Guo, Jian Zhang, Qing Chen, Ziyuan Gu

“…In this paper, through the integration of deep learning and stereo vision technology, the growth pattern and attitude of apples in the natural environment are identified, and three-dimensional spatial positioning is realized. …”
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Deep Learning Method for Classifying Items into Categories for Dutch Auctions by Janusz Bobulski, Sabina Szymoniak

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Deep learning-based near-field effect correction method for Controlled Source Electromagnetic Method and application by Wei Luo, Xianjie Chen, Shixing Wang, Siwei Zhao, Xiaokang Yin, Xing Lan, Peifan Jiang, Shaojun Wang

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Research on Tongue Image Segmentation and Classification Methods Based on Deep Learning and Machine Learning by Bin Liu, Zeya Wang, Kang Yu, Yunfeng Wang, Haiying Zhang, Tingting Song, Hao Yang

“…In this study, we propose a tongue image segmentation method based on deep learning and a pixel-level tongue color classification method utilizing machine learning techniques such as support vector machine (SVM) and ridge regression. …”
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An efficient leukemia prediction method using machine learning and deep learning with selected features. by Mahwish Ilyas, Muhammad Ramzan, Mohamed Deriche, Khalid Mahmood, Anam Naz

“…Deep learning methods have been shown to outperform traditional methods in leukemia gene classification by utilizing specific features.…”
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