“…By utilizing the object detection framework Mask R-CNN, the nematodes are located, classified, and their contours predicted. …”
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“…The ViT-CNN ensemble model is an ensemble model that combines the vision transformer model and convolutional neural network (CNN) model. …”
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“…Model MC1 is a 2-layer CNN with global average pooling, followed by a dense layer. …”
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“…The proposed CNN is also trained and tested with the MNIST handwritten data set. …”
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“…The performance of the CNN and image retrieval algorithms were improved by transfer learning and hashing functions. …”
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“…In this paper, we propose a novel deep learning architecture called ResMem-Net that is a hybrid of LSTM and CNN that uses information from the hidden layers of the CNN to compute the memorability score of an image. …”
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“…Therefore, this paper proposes a multi-label text classification method based on tALBERT-CNN: an LDA topic model and ALBERT model are used to obtain the topic vector and semantic context vector of each word (document), a certain fusion mechanism is adopted to obtain in-depth topic and semantic representations of the document, and the multi-label features of the text are extracted through the TextCNN model to train a multi-label classifier. …”
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“…In this work, we demonstrate that high-quality images can be reconstructed by applying the recently proposed Mixed Scale Dense (MS-D) convolutional neural network (CNN) to this task. We also propose a novel training approach by which training data are acquired as part of each scan, thus removing the need for large sets of pre-existing reference data, the acquisition of which is often not practicable or possible. …”
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“…This study proposes a convolutional neural network known as the signal filtering convolutional neural network (SF-CNN) to handle precipitation intensity using surveillance-based images. …”
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“…In this paper, locating and routing the lost gamma source in the gamma irradiation room containing radiation blocking barriers are done simultaneously by using two methods, convolutional neural network (CNN) and Q-learning, which are powerful algorithms for deep learning and machine learning. …”
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“…Through fast region-based convolutional neural networks (R-CNN), a deep learning method that recognizes vector-based information, a model to assist in the diagnosis of depressive disorder can be devised by checking the position change of the eyes and lips, and guessing emotions based on accumulated photos of the participants who will repeatedly participate in the diagnosis of depressive disorder.…”
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“…Particularly, we propose a hybrid 2D–3D CNN architecture capable of obtaining semantic segmentation and depth estimation at the same time. …”
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“…This paper presents the evaluation of 36 convolutional neural network (CNN) models, which were trained on the same dataset (ImageNet). …”
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“…To address these challenges, this study presents CODISC-CNN (CNN based Coronavirus DIsease Prediction System for Chest X-rays) that can automatically extract the features from chest X-ray images for the disease prediction. …”
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“…In this study, the application of an instance segmentation method based on region proposal architecture, called the Mask R-CNN, is explored in depth in the context of retinal OCT image segmentation. …”
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“…The current study proposed a deep convolutional neural network (CNN) with support vector machine (SVM) classifier which aims to improve the classification accuracy of winter rape seeding and weeds in fields. …”
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“…This article proposes a two-stage convolutional neural network model for joint demosaicing and denoising of burst Bayer images. The proposed CNN model consists of a single-frame joint demosaicing and denoising module, a multiframe denoising module, and an optional noise estimation module. …”
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