A Novel Pattern Recognition Method for Self-Powered TENG Sensor Embedded to the Robotic Hand by Azat Balapan, Rauan Yeralkhan, Alikhan Aryslanov, Gulnur Kalimuldina, Azamat Yeshmukhametov

“…Experimental results demonstrate that the proposed 2D CNN method significantly improves shape and material recognition accuracy, achieving 98% and 99%, respectively, compared to 94% and 98% with the 1D CNN method. …”
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Cerebral Arterial Stenosis Detection Based on a Retained Two-Stage Detection Algorithm by Hanqing Liu, Xiaojun Li, Jin Wei, Xiaodong Kang

“…A retrained two-stage algorithm for detecting cerebral arterial stenosis in CTA images is proposed to solve these problems by further fusing image features and improving the quality of regions of interest. In Faster R-CNN and Libra R-CNN, the backbone network was Resnet50, with deformable convolutional and nonlocal neural networks introduced in the third, fourth, and fifth stages of the backbone network. …”
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A novel data augmentation tool for enhancing machine learning classification: A new application of the higher order dynamic mode decomposition for improved cardiac disease identifi... by Nourelhouda Groun, María Villalba-Orero, Lucía Casado-Martín, Enrique Lara-Pezzi, Eusebio Valero, Jesús Garicano-Mena, Soledad Le Clainche

“…Six sets of the original echocardiography databases were hold out to be used as unseen data to test the performance of the CNN. In order to demonstrate the efficiency of the HODMD technique, two testcases are studied: the CNN is first trained using the original echocardiography images only, and second training the CNN using a combination of the original images and the DMD modes. …”
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Lung cancer Prediction and Classification based on Correlation Selection method Using Machine Learning Techniques by Dakhaz Mustafa Abdullah, Adnan Mohsin Abdulazeez, Amira Bibo Sallow

“…The experimental results show that SVM gives the best result with 95.56%, then CNN with CNN 92.11% and KNN with 88.40%. …”
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Learning-Based Path Planning Algorithm in Ocean Currents for Multi-Glider by Wei Lan, Xiang Jin, Xin Chang, Tianlin Wang, Han Zhou

“…The results show that the path planning problem of glider formation in ocean currents can be solved by using Doc-CNN.…”
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Model Deep Learning Untuk Klasifikasi Objek Pada Gambar Fisheye by Riza Ayu Putri, Arief Suryadi Satyawan, Johanes Adi Prihantono, Rinda Safana Linggi, I Gusti Ayu Putri Surya Paramita, Ni Kadek Emy Iswarawati, Fabian Akbar, Prio Adjie Utomo

“…Metode pengenalan objek yang digunakan yaitu deep learning dengan arsitektur CNN (Convolution Neural Network). CNN memiliki kemampuan untuk mengenali objek dalam gambar. …”
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Compound Fault Diagnosis for Gearbox Based Using of Euclidean Matrix Sample Entropy and One-Dimensional Convolutional Neural Network by Decai Zhang, Xueping Ren, Hanyue Zuo

“…Finally, the PFs by MESE are used to train the CNN to identify the faults of parallel-shaft gearbox. …”
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Deep Transfer Learning for Lip Reading Based on NASNetMobile Pretrained Model in Wild Dataset by Ashwaq Waleed Abdul Ameer, Pedram Salehpour, Mohammad Asadpour

“…The proposed framework involves a process that extracts features from video frames in a time sequence, employing methods such as Convolutional Neural Networks (CNN), CNN-Gated Recurrent Units (CNN-GRU), Temporal CNN, and Temporal PoinWise. …”
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Automatic Detection of Cracks in Cracked Tooth Based on Binary Classification Convolutional Neural Networks by Juncheng Guo, Yuyan Wu, Lizhi Chen, Guanghua Ge, Yadong Tang, Wenlong Wang

“…A CNN model is designed by modifying the size of the input layer and adding a fully connected layer with 2 units based on the ResNet50, and then, the proposed CNN is trained and validated with a self-prepared cracked tooth dataset including 20,000 images. …”
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Convolutional neural networks for diabetic retinopathy detection by Darwin Patiño-Pérez, Luis Armijos-Valarezo, Luis Chóez-Acosta, Freddy Burgos-Robalino

“…This study evaluates and compares the performance of three convolutional neural network (CNN) architectures ResNet-18, ResNet-50, and a custom, non-pretrained CNN using a dataset of retinal images classified into five categories. …”
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Malaria Diagnosis Using a Lightweight Deep Convolutional Neural Network by Varun Magotra, Mukesh Kumar Rohil

“…The application of convolutional neural network (CNN) and mask-region-based CNN (Mask-RCCN) to the medical domain has really revolutionized medical image analysis. …”
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Assessing Deep Learning Techniques for the Recognition of Tropical Disease in Images from Parasitological Exams by Ammar Akram Abdulrazzaq, Asaad T. Al-Douri, Abdulsattar Abdullah Hamad, Mustafa Musa Jaber, Zelalem Meraf

“…The results obtained in a real database indicate that the techniques are effective in the recognition of schistosomiasis eggs, in which both obtained AUC (area under the curve) above 0.90, with the CNN showing superiority in this aspect. . However, the SPNN proved to be faster than the CNN.…”
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Development of Deep Convolutional Neural Network with Adaptive Batch Normalization Algorithm for Bearing Fault Diagnosis by Chao Fu, Qing Lv, Hsiung-Cheng Lin

“…They, however, may suffer from time-consuming and low versatility. In this paper, a CNN integrated with the adaptive batch normalization (ABN) algorithm (ABN-CNN) is developed to avoid high computing resource requirements of such complex networks. …”
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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

“…Untuk menguji metode CNN, digunakan berbagai variasi cahaya sebesar 10-200 lux, serta jarak dari tangan ke webcam 50-200 cm. …”
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Spatial Downscaling of Daily Temperature Minima Using Machine Learning Methods and Application to Frost Forecasting in Two Alpine Valleys by Sudheer Bhakare, Michael Matiu, Alice Crespi, Dino Zardi

“…This study examines the performance of three machine learning models—namely, Artificial Neural Network (ANN), Random Forest (RF), and Convolutional Neural Network (CNN)—for spatial downscaling of seasonal forecasts of daily minimum temperature from 12 km to 250 m horizontal resolution. …”
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Improving multi-talker binaural DOA estimation by combining periodicity and spatial features in convolutional neural networks by Reza Varzandeh, Simon Doclo, Volker Hohmann

“…The two-stage CNN incorporates a PD feature reduction stage prior to the joint processing of PD and CPS phase features. …”
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FPGA-QNN: Quantized Neural Network Hardware Acceleration on FPGAs by Mustafa Tasci, Ayhan Istanbullu, Vedat Tumen, Selahattin Kosunalp

“…The performance of a typical CNN model can be enhanced by the improvement of hardware accelerators. …”
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Bayesian deep learning applied to diabetic retinopathy with uncertainty quantification by Masoud Muhammed Hassan, Halbast Rashid Ismail

“…In this paper, we developed a straightforward architecture for the classification of DR using a Convolutional Neural Network (CNN) model. We then applied the Bayesian CNN twice, once using Variational Inference (VI) and once using Monte Carlo dropout (MC-dropout) methods, to the same CNN architecture. …”
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A systematic assessment of sentiment analysis models on iraqi dialect-based texts by Hafedh Hameed Hussein, Amir Lakizadeh

“…This study proposes hybrid models combining Convolutional Neural Networks with Long Short-Term Memory called as CNN-LSTM, CNN with Gated Recurrent Unit called as CNN-GRU. and AraBERT, a deep transformer model, to enhance Iraqi sentiment analysis. …”
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Optimization of Sample Size, Data Points, and Data Augmentation Stride in Vibration Signal Analysis for Deep Learning-Based Fault Diagnosis of Rotating Machines by Fasikaw Kibrete, Dereje Engida Woldemichael, Hailu Shimels Gebremedhen

“…This study utilizes a one-dimensional convolutional neural network (1-D CNN) as the deep learning model for fault classification. …”
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