“…We developed a convolutional neural network (CNN) to distinguish these tumors on contrast-enhanced T(1)-weighted images. …”
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“…METHODS: This approach was carried out using a Convolutional Neural Network (CNN) based structure for semantic segmentation and a subsequent elaboration of the obtained output, which produced the needed parameters for attaching the 3D model. …”
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“…METHODS: The data set included 2482 anonymized panoramic radiographs from adults from the archive of Eskisehir Osmangazi University, Faculty of Dentistry, Department of Oral and Maxillofacial Radiology. A Faster R-CNN Inception v2 model was used to develop an AI algorithm (CranioCatch, Eskisehir, Turkey) to automatically detect and number teeth on panoramic radiographs. …”
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“…It is observed through experiments that the proposed DBHL framework, which merges the two-deep CNN feature spaces, yields good performance (accuracy: 98.53%, sensitivity: 0.99, F-score: 0.98, and precision: 0.98). …”
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“…We systematically characterized the effects of image denoising on empirical data acquired at 0.6 mm isotropic resolution using three classical denoising methods, including denoising convolutional neural network (DnCNN), block-matching and 4-dimensional filtering (BM4D) and adaptive optimized non-local means (AONLM). …”
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“…To do this, a convolutional neural network (CNN) was trained to learn cyst edges and cyst cores. …”
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“…In this paper, a two-stage deep CNN based scheme is proposed to detect COVID-19 from chest X-ray images for achieving optimum performance with limited training images. …”
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“…We developed a convolutional neural network (CNN) with a DenseNet architecture pre-trained on ImageNet as a feature extractor on our data and trained a classifier uniquely tailored for identification of AO and non-AO images using binary cross entropy loss. …”
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“…Second, it uses a time-distributed convolutional neural network (CNN) to integrate and map the feature matrices to feature vectors. …”
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“…Furthermore, we performed extensive experiments by implementing RNN-LSTM, RNN-BiLSTM and CNN models varying epochs executions, model layers and tuning hyperparameters to analyze and uncover cyberbullying textual patterns in Roman Urdu. …”
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“…The sensitivity and specificity of the complex domain analysis algorithm for the detection of epilepsy EEG were much higher than those of the EEG automatic detection algorithm based on time-domain waveform similarity and the EEG automatic detection algorithm based on convolutional neural network (CNN), and the average running time was opposite, showing obvious difference (P < 0.05).The average accuracy, sensitivity, and specificity of children in the experimental group were 96.11%, 97.10%, and 95.19%, respectively; and those in the control group were 88.83%, 90.14%, and 87.82%, respectively, so there was an obvious difference in accuracy between two groups (P < 0.05). …”
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“…The artificial intelligence (AI) algorithm, a CNN developed by MoleMap Ltd and Monash eResearch, classifies lesions as benign, malignant or uncertain. …”
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“…In summary, the network model based on the deep learning algorithm can remove the artifacts in DSA images and present high-quality clear images, and convolutional neural network (CNN) algorithms had a strong ability to automatically learn features in the field of medical image processing and were worthy of being widely used and popularized. …”
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“…A faster region-convolutional neural network (Faster R-CNN), feature pyramid network (FPN), single shot multibox detector (SSD), and You Only Look Once (YOLOv3) were employed for bean pods recognition in which recognition precision and speed were 86.2, 89.8, 80.1, 87.4%, and 13 frames per second (FPS), 7 FPS, 24 FPS, and 39 FPS, respectively. …”
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“…Keywords: MRI, Breast, Segmentation, Supervised Learning, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms Published under a CC BY 4.0 license. …”
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“…This study aims to build a deep convolutional neural network (CNN) for the automatic classification of metastatic malignancies involving thoracic LN, using EBUS-TBNA. …”
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“…Deep learning-based artificial intelligence (AI) algorithms using convolutional neural networks (CNN) were applied to detect and classify pulmonary nodules (PNs). …”
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“…A deep convolutional neural network (CNN) was used to evaluate OVD layer thickness based on the B-scans. …”
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“…Abbreviations: Aa, amino acids; CHO, Chinese hamster ovary; CNN, convolutional neural network; CSscore, cleavage site score; CSV, comma-separated values; HC, heavy chain; HEK, human embryonic kidney; HPLC, high-performance liquid chromatography; IgG, immunoglobulin G; IGLV, immunoglobulin G Lambda variable; LC, light chain; LCMS, liquid chromatography–mass spectrometry; MS, mass spectrometry; PCR, polymerase chain reaction; PBS, phosphate-buffered saline; PEI, polyethylenimine; SP, signal peptide; SPase, signal peptidase; TCEP, tris(2-carboxyethyl) phosphine; TOF, time-of-flight.…”
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“…The Dice, HD, and PAD values of the ML-Net algorithm were all statistically different from those of the convolutional neural networks (CNN), fully convolutional networks (FCN), SegNet, and U-Net algorithms (P < 0.05). …”
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