The application of series multi-pooling convolutional neural networks for medical image segmentation by Feng Wang, Siwei Huang, Lei Shi, Weiguo Fan

“…To solve the said problems, the model of convolutional neural network in the deep learning approach was used in this article to cope with classification and labeling tasks of brain tumor images. …”
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Facial Expression Recognition Using a Novel Modeling of Combined Gray Local Binary Pattern by An H. Ton-That, Nhan T. Cao

“…Facial Expression Recognition (FER) is an active research field at present. Deep learning is a good method that is widely used in this field but it has extreme hardware requirements and it is hard to apply in normal terminal devices. …”
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Vietnamese Sentiment Analysis under Limited Training Data Based on Deep Neural Networks by Huu-Thanh Duong, Tram-Anh Nguyen-Thi, Vinh Truong Hoang

“…Several experiments have been performed for both well-known machine learning-based classifiers and deep learning models. We compare, analyze, and evaluate the results to indicate the advantage and disadvantage points of the techniques for each approach. …”
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Intelligent Computer Technology-Driven Mural Pattern Recognition Method by Wenqing Wei, Lei Gao

“…In recent years, as a new image processing technology, deep learning based on a convolutional neural network is widely used in many fields. …”
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Automatic detection and prediction of COVID-19 in cough audio signals using coronavirus herd immunity optimizer algorithm by G. Ayappan, S. Anila

“…This study proposes an advanced framework to detect and predict COVID-19 using deep learning from cough audio signals. Audio data from the COUGHVID dataset undergo preprocessing through fuzzy gray level difference histogram equalization, followed by segmentation with a U-Net model. …”
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Current Trends in Class Imbalance Learning for Software Defect Prediction by Somya R. Goyal

“…Among the available evaluation metrics, Area under the Curve is the most used one as it is insulated from the impact of imbalanced datasets. Deep learning models have potential and prospects to be explored for class imbalance handling in SDP in a full-fledged capacity.…”
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Sistem Rekognisi Citra Digital Bahasa Isyarat Menggunakan Convolutional Neural Network dan Spatial Transformer by Mohammad Alfiano Rizky Mahardika, Novanto Yudistira, Achmad Ridok

“…Dengan menggunakan metode Convolutional Neural Network (CNN) yang merupakan bagian dari Deep Learning atau Machine Learning, sistem akan mengenali pose atau bentuk dari citra bahasa isyarat yang dimasukkan, dan memberikan luaran yang sesuai dengan maksud dari pose atau bentuk dari citra bahasa isyarat tersebut. …”
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A BigBiGAN-Based Loop Closure Detection Algorithm for Indoor Visual SLAM by Qiubo Zhong, Xiaoyi Fang

“…The majority of loop detection methods extract artificial features, which fall short of learning comprehensive data information, but unsupervised learning as a typical deep learning method excels in self-access learning and clustering to analyze the similarity without handling the data. …”
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A Detection Method Against Load Redistribution Attacks in the Interdependence of the Natural Gas Network and Power System Based on Entropy by Yaoying Wang

“…Instead of relying on deep learning algorithms, this study leverages entropy-based techniques for attack detection. …”
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A dataset of annotated African plum images from Cameroon for AI-based quality assessmentKaggle by Arnaud Nguembang Fadja, Armel Gabin Fameni Tagni, Sain Rigobert Che, Marcellin Atemkeng

“…This resource is valuable for developing and testing computer vision, deep learning-based recognition systems and object detection models in agriculture, enabling automated evaluation of plum quality for commercialization. …”
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DETECTING WEB-BASED BOTNETS USING A WEB PROXY AND A CONVOLUTIONAL NEURAL NETWORK by Trần Đắc Tốt, Phạm Tuấn Khiêm, Phạm Nguyễn Huy Phương

“…We experimented on the CTU-13 dataset using different configurations of the convolutional neural network to evaluate the potential of deep learning on the botnet detection problem. In particular, we propose a botnet detection system that uses a web proxy. …”
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A Scoping Review of the Smart Irrigation Literature Using Scientometric Analysis by Daraje Kaba Gurmessa, Shimelis G. Assefa

“…The leading main topics addressed in the field are IOT, smart irrigation, irrigation, water stress, energy, deep learning, soil moisture, and relations in the network. …”
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Severity Classification of Conjunctival Hyperaemia by Deep Neural Network Ensembles by Hiroki Masumoto, Hitoshi Tabuchi, Tsuyoshi Yoneda, Shunsuke Nakakura, Hideharu Ohsugi, Tamaki Sumi, Atsuki Fukushima

“…Neural networks and deep learning have been utilised in ophthalmology, but not for the purpose of classifying the severity of conjunctival hyperaemia objectively. …”
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An Approach of Community Search with Minimum Spanning Tree Based on Node Embedding by Jinglian Liu, Daling Wang, Shi Feng, Yifei Zhang

“…Node embedding uses deep learning method to obtain feature representation of nodes directly from graph structure automatically and offers a new method to measure the distance between two nodes. …”
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Detection of Fungal Infections in Gloriosa Superba Plant Using the Convolution Neural Network Model by Guillermo Napoleón Pelaez-Diaz, Rosa Vílchez-Vásquez, Antonio Huaman-Osorio, R. Mahaveerakannan, S. Pushpa, Nilesh Shelke, Sumitha Jagadibabu, Jenifer Mahilraj

“…The money plant is also known as the Gloriosa superba. We used a deep learning-based convolution neural network (CNN) classifier model to optimize the CNN algorithm parameter for better prediction. …”
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STAIG: Spatial transcriptomics analysis via image-aided graph contrastive learning for domain exploration and alignment-free integration by Yitao Yang, Yang Cui, Xin Zeng, Yubo Zhang, Martin Loza, Sung-Joon Park, Kenta Nakai

“…Here, we propose STAIG, a deep-learning model that integrates gene expression, spatial coordinates, and histological images using graph-contrastive learning coupled with high-performance feature extraction. …”
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Transfer Learning for CNN-Based Damage Detection in Civil Structures with Insufficient Data by Mona Chamangard, Gholamreza Ghodrati Amiri, Ehsan Darvishan, Zahra Rastin

“…Among various methods proposed for health monitoring of structures, deep learning-based techniques with their powerful performance have attracted considerable attention in recent years. …”
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Drone Landing and Reinforcement Learning: State-of-Art, Challenges and Opportunities by Jose Amendola, Linga Reddy Cenkeramaddi, Ajit Jha

“…Finally, we present our critical analysis of how recent state-of-the-art deep learning concepts can be combined with reinforcement learning to leverage the latter in addressing the open gaps in future works.…”
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A Vortex Identification Method Based on Extreme Learning Machine by Jun Wang, Lei Guo, Yueqing Wang, Liang Deng, Fang Wang, Tong Li

“…Recently, proposed deep learning methods have long network training time and high computational complexity. …”
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Arrhythmia Classification Techniques Using Deep Neural Network by Ali Haider Khan, Muzammil Hussain, Muhammad Kamran Malik

“…The automated systems that can be adapted as a tool for screening arrhythmia classification play a vital role not only for the patients but can also assist the doctors. The deep learning-based automated arrhythmia classification techniques are developed with high accuracy results but still not adopted by healthcare professionals as the generalized approach. …”
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