Classification of Some Barley Cultivars with Deep Convolutional Neural Networks by Fatih Bayram, Mustafa Yıldız

“…In this research, a novel image database consisting of 2800 images were created to classify 14 barley cultivars. Six different deep convolutional neural network models were designed based on a transfer learning method with pretrained DenseNet-121, DenseNet-169, DenseNet-201, InceptionResNetV2, MobileNetV2 and Xception networks. …”
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Golf swing classification with multiple deep convolutional neural networks by Libin Jiao, Rongfang Bie, Hao Wu, Yu Wei, Jixin Ma, Anton Umek, Anton Kos

“…In this article, we investigate golf swing data classification methods based on varieties of representative convolutional neural networks (deep convolutional neural networks) which are fed with swing data from embedded multi-sensors, to group the multi-channel golf swing data labeled by hybrid categories from different golf players and swing shapes. …”
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Brain tumor classification using deep convolutional neural networks by M. Nurtay, M. Kissina, A. Tau, A. Akhmetov, G. Alina, N. Mutovina

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A Cascade of Encoder–Decoder with Atrous Convolution and Ensemble Deep Convolutional Neural Networks for Tuberculosis Detection by Noppadol Maneerat, Athasart Narkthewan, Kazuhiko Hamamoto

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Combining Convolutional Neural Networks for Fungi Classification by Anuruk Prommakhot, Jakkree Srinonchat

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Convolutional Neural Networks for Predicting Power Outages in Baghdad by Saja Jafar Jawad, Shaymaa. W. Al-Shammari

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An adaptive filter for anemia screening using deep convolutional neural network by Jose B. Lazaro, Jr., Jennifer C. Dela Cruz, Jocelyn F. Villaverde

“…This study introduces an automated anemia detection system powered by deep convolutional neural networks (DCNNs), CMOS image sensing, Adam optimizer, and multi-scale feature extraction (MSFE) to improve diagnostic precision and accessibility. …”
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ANALYSIS OF EMOTION RECOGNITION BASED ON DEEP CONVOLUTIONAL NEURAL NETWORK MODELS by V. M. Goryaev, G. A. Mankaeva, T. B. Ochir-Goryaeva, A. B. Mantusov, V. V. Lidji-Garyaev, A. B. Kornyakov

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Image Recognition Based on Multiscale Pooling Deep Convolution Neural Networks by Haitao Sang, Li Xiang, Shifeng Chen, Bo Chen, Li Yan

“…To achieve this, through making full use of block information of different sizes and scales in the image, a multiscale pooling deep convolution neural network model is designed in this paper. …”
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Classification of Cavendish Banana Quality using Convolutional Neural Network by Ajeng Ayu Suryani, Ummi Athiyah, Yohani Setiya Rafika Nur, Warto

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Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment by Dhanadeepika B., Vanithasri M., Chakravarthi M.

“…This work introduces a CM approach using Deep Convolution Neural Network (DCNN) for minimizing congestion and supporting Independent System Operators (ISOs). …”
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Leveraging Deep Learning and Convolutional Neural Network for Digital Waste Image Classification by Fauzan Naufal Anis, Sukmasetya Pristi, Nuryanto Nuryanto

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Using deep convolutional neural networks to forecast spatial patterns of Amazonian deforestation by James G. C. Ball, Katerina Petrova, David A. Coomes, Seth Flaxman

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Deep Learning-Based Interference Fringes Detection Using Convolutional Neural Network by Haowei Li, Chunxi Zhang, Ningfang Song, Huipeng Li

“…The FRPN, a deep convolutional neural network modified on Faster R-CNN, accurately recognizes the fringes with identification boxes. …”
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Error Bounds for Approximations Using Multichannel Deep Convolutional Neural Networks with Downsampling by Xinling Liu, Jingyao Hou

“…However, what is primarily called into question by people is its lack of theoretical foundation investigations, especially for structured neural networks. This paper theoretically studies the multichannel deep convolutional neural networks equipped with the downsampling operator, which is frequently used in applications. …”
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High-Performance Character Recognition System Utilizing Deep Convolutional Neural Networks by Duaa Mowafak Hameed, Raid Rafi Omar Al-Nima

“…Following acquisition, the input images undergo preparation, segmentation, and resizing. After that, a Deep Convolutional Neural Network (DCNN) is used to recognize letters from them. …”
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DeepCNNMed: Enhancing Medicinal Plant Identification Through Deep Convolutional and Hybrid Neural Networks by Rajalakshmi Gurusamy, Parameswari Chandrasekaran, Yamuna Devi Manickam Malu, Madhusudhanan Sampath, Nesarani Abraham

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Speaker Identification and Verification Using Convolutional Neural Network CNN by Azhar S. Abdulaziz, Akram Dawood, Amar Daood

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Morphological and spectral analysis of histological tissue with the use of deep convolutional networks by S. V. Trukhan, A. M. Nedzved, A. Kohler

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Lung Nodule Classification Based on 3D Convolutional Neural Network by WANG Wei-bing, WANG Zhuo, XU Qian, SUN Hong

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