CNN-Trans-SPP: A small Transformer with CNN for stock price prediction by Ying Li, Xiangrong Wang, Yanhui Guo

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DDL R-CNN: Dynamic Direction Learning R-CNN for Rotated Object Detection by Weixian Su, Donglin Jing

“…To address these challenges, this paper introduces a novel approach known as Dynamic Direction Learning R-CNN (DDL R-CNN), which comprises a dynamic direction learning (DDL) module and a boundary center region offset generation network (BC-ROPN). …”
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MSRD-CNN: Multi-Scale Residual Deep CNN for General-Purpose Image Manipulation Detection by Kapil Rana, Gurinder Singh, Puneet Goyal

“…In this paper, a novel Multi-Scale Residual Deep CNN (MSRD-CNN) is designed to learn the image manipulation features adaptively for multiple image manipulation detection. …”
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Relation extraction based on CNN and Bi-LSTM by Xiaobin ZHANG, Fucai CHEN, Ruiyang HUANG

“…Relation extraction aims to identify the entities in the Web text and extract the implicit relationships between entities in the text.Studies have shown that deep neural networks are feasible for relation extraction tasks and are superior to traditional methods.Most of the current relation extraction methods apply convolutional neural network (CNN) and long short-term memory neural network (LSTM) methods.However,CNN just considers the correlation between consecutive words and ignores the correlation between discontinuous words.On the other side,although LSTM takes correlation between long-distance words into account,the extraction features are not sufficiently extracted.In order to solve these problems,a relation extraction method that combining CNN and LSTM was proposed.three methods were used to carry out the experiments,and confirmed the effectiveness of these methods,which had some improvement in F1 score.…”
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Network traffic classification method basing on CNN by Yong WANG, Huiyi ZHOU, Hao FENG, Miao YE, Wenlong KE

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Continuous speech speaker recognition based on CNN by Zhendong WU, Shucheng PAN, Jianwu ZHANG

“…Then input the voiceprint extract from CNN model to a reward-penalty function to continuous measurement. …”
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Network traffic monitoring based on CNN-SVM by Wu Qian

“…CNN has the ability to recognize intricate patterns in the data and automatically extract valuable characteristics from the raw data. …”
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Tuberculosis Classification using SVM and Modified CNN by SRINIVAS BABU N, SHASHIKIRAN S, M JAYANTHI, Rajani N, K M PALANISWAMY, M R KUSHALATHA

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Classification of Coconut Trees Within Plantations from UAV Images Using Deep Learning with Faster R-CNN and Mask R-CNN by Morakot Worachairungreung, Nayot Kulpanich, Pornperm Sae-ngow, Kunyaphat Thanakunwutthirot, Kawinphop Anurak, Phonpat Hemwan

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Research on Fault Diagnosis Method Based on Improved CNN by Hu Hao, Feng Fuzhou, Zhu Junzhen, Zhou Xun, Jiang Pengcheng, Jiang Feng, Xue Jun, Li Yazhi, Sun Guanghui

“…To solve these problems, a fault diagnosis method based on an improved convolutional neural network (CNN) is proposed. Based on the traditional CNN model, a variety of convolution stride modes were added to extract features of different scales of signals and expand the feature dimension. …”
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Adaptive CNN Ensemble for Complex Multispectral Image Analysis by Syed Muslim Jameel, Manzoor Ahmed Hashmani, Mobashar Rehman, Arif Budiman

“…The adaptive CNN ensemble framework consists of five (05) modules, including dynamic ensemble classifier (DEC) module. …”
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Approximate CNN Hardware Accelerators for Resource Constrained Devices by P Thejaswini, Gautham Suresh, V. Chiraag, Sukumar Nandi

“…In this paper, we propose a modular pipelined Feedforward CNN Hardware Accelerator (FHA) and a novel Approximate Feedforward CNN Hardware Accelerator (AFHA). …”
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Designing an Efficient System for Emotion Recognition Using CNN by Donia Ammous, Achraf Chabbouh, Awatef Edhib, Ahmed Chaari, Fahmi Kammoun, Nouri Masmoudi

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Comparative analysis of CNN models for handwritten digit recognition by Krystyna Banaszewska, Małgorzata Plechawska-Wójcik

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Bearing fault diagnosis method based on SAVMD and CNN by SONG ChunSheng, LIANG YaRu, LU NiFang, DU Gang, JIA Bo

“…The intrinsic mode function (IMF) components were reconstructed by weighted kurtosis evaluation index, put them into convolutional neural network (CNN) model for fault classification. Finally, the proposed method was verified by numerical simulations with the open bearing data of Case Western Reserve University. …”
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Feature Guided CNN for Baby’s Facial Expression Recognition by Qing Lin, Ruili He, Peihe Jiang

“…We also propose a feature guided CNN method with a new loss function, called distance loss, to optimize interclass distance. …”
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Efficient Pattern Recognition of Sundanese Script Variants Using CNN by Muhammad Husni Wahid, Erik Iman Heri Ujianto

Subjects: “…cnn…”
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Advancements in CNN Architectures for Offline Handwritten Arabic Character Recognition by El Ibrahimi Aissam, Elzaar Abdellah, El Akchioui Nabil, Benaya Nabil, El Allati Abderrahim

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Prediction of Bearing Remaining Service Life Based on CNN-LSTM by Cai Weiwei, Xu Yanwei, Xie Tancheng

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FAULT DIAGNOSIS METHOD OF ROLLING BEARING BASED ON EEMD-CNN by LI SiQi, JIANG ZhiJian

“…In order to improve the rolling bearing fault diagnosis accuracy,this paper presents a fault diagnosis method based on Ensemble Empirical Mode Decomposition（ EEMD） and Convolution Neural Networks（ CNN）. At first,using the EEMD decompose the signal. …”
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