Deep transfer learning
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In this study, we explore the potential of graph neural networks (GNNs), in combination with transfer learning, for the prediction of molecular solubility, a crucial property in drug discovery and materials science. Our approach begins with the development of a GNN-based model to predict the dipole moment of molecules.
8p viwalton 02-07-2024 1 0 Download
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This paper presents an RTL (Register Transfer Logic) level microarchitecture of hardware-and bandwidth-efficient high-performance 2D convolution unit for CNN in deep learning. The 2D convolution unit is made up of three main components including a dedicated Loader, a Circle Buffer, and a MAC (Multiplier-Accumulator) unit.
13p viambani 18-06-2024 2 1 Download
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We propose DEGAS (Diagnostic Evidence GAuge of Single cells), a novel deep transfer learning framework, to transfer disease information from patients to cells. We call such transferrable information “impressions,” which allow individual cells to be associated with disease attributes like diagnosis, prognosis, and response to therapy.
23p viellison 28-03-2024 3 2 Download
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T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, which has sparked interest in the development of various T-cell-focused immunotherapies.
24p vicwell 29-02-2024 2 1 Download
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This study introduces an approach to detect deepfake images using transfer learning methods, including XceptionNet, RestNet101, InceptionResV2, MobileNetv2, VGG19 and DenseNet121, along with comparing it with a traditional CNN model.
8p vigrab 02-02-2024 6 3 Download
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Prostate cancer is often a slowly progressive indolent disease. Unnecessary treatments from overdiagnosis are a significant concern, particularly low-grade disease. Active surveillance has being considered as a risk management strategy to avoid potential side effects by unnecessary radical treatment.
18p vileonardodavinci 23-12-2023 5 3 Download
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One of the emerging research trends in natural language understanding is machine reading comprehension (MRC) which is the task to find answers to human questions based on textual data. Existing Vietnamese datasets for MRC research concentrate solely on answerable questions.
16p viberkshire 09-08-2023 5 3 Download
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Despite of the strong development of OTT message applications and social networks, Short Service Message (SMS) keeps its undeniable role in the marketing industry. As a top level of effective and cost-saving advertising tool, SMS has also given rise to SMS spam.
5p viannee 02-08-2023 6 5 Download
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Multitask learning (MTL) using electronic health records allows concurrent prediction of multiple endpoints. MTL has shown promise in improving model performance and training efficiency; however, it often suffers from negative transfer – impaired learning if tasks are not appropriately selected.
11p vighostrider 25-05-2023 4 2 Download
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The aim of study "A smart agricultural application: automated detection of diseases in vine leaves using hybrid deep learning" is to improve diseasedetection accuracy in vine leaves and to develop a system to help Syrian and Turkish farmers and agricultural engineers to maintain the quality of grape production. In this study, over 1000 images of vine leaves have been collected from vine yards in Syria and the internet.
14p lyhuyenthu 31-01-2023 8 2 Download
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The present paper "Apple leaf disease detection and classification based on transfer learning" introduces a new approach to transfer learning in that training, validating and testing of the model have been made on images from different sources to see its effectiveness. Several optimization methods including the adaptation of a recent custom PowerSign optimization algorithm are compared in the study.
10p lyhuyenthu 31-01-2023 4 2 Download
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In this paper, the framework of polyp image segmentation is developed by a deep learning approach, especially a convolutional neural network. The proposed framework is based on improved Unet architecture to obtain the segmented polyp image.
15p visirius 19-01-2023 10 4 Download
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Bài viết đề xuất một mô hình tổng hợp tiếng nói tiếng Việt dựa trên việc áp dụng phương pháp Transfer Learning vào mô hình Deep Convolution Neural Network để sinh ra tiếng nói mới dựa trên tập dữ liệu huấn luyện rất nhỏ. Mô hình của chúng tôi có thể tổng hợp giọng nói mới với lượng dữ liệu huấn luyện nhỏ hơn 45 lần so với khi dùng mô hình Tacotron 2.
6p vistephenhawking 26-04-2022 47 3 Download
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Colonoscopy image classification is an image classification task that predicts whether colonoscopy images contain polyps or not. It is an important task input for an automatic polyp detection system. Recently, deep neural networks have been widely used for colonoscopy image classification due to the automatic feature extraction with high accuracy.
11p vikissinger 03-03-2022 11 1 Download
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To fully utilize the power of single-cell RNA sequencing (scRNA-seq) technologies for identifying cell lineages and bona fide transcriptional signals, it is necessary to combine data from multiple experiments. We present BERMUDA (Batch Effect ReMoval Using Deep Autoencoders), a novel transfer-learning-based method for batch effect correction in scRNA-seq data.
15p vielonmusk 30-01-2022 13 0 Download
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Classification of rocks is one of the basic parts of geological research and is a difficult task due to the heterogeneous properties of rocks. This process is time consuming and requires sufficiently knowledgeable and experienced specialists in the field of petrography. This paper has a novelty in classifying plutonic rock types for the first time using thin section images; and proposes an approach that uses the deep learning method for automatic classification of 12 types of plutonic rocks.
10p tanmocphong 29-01-2022 9 1 Download
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Deep learning has proven to be a powerful technique for transcription factor (TF) binding prediction but requires large training datasets. Transfer learning can reduce the amount of data required for deep learning, while improving overall model performance, compared to training a separate model for each new task.
25p viarchimedes 26-01-2022 12 0 Download
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Although genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive.
27p viarchimedes 26-01-2022 11 0 Download
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. In this paper, we survey deep transfer learning models with a focus on applications to text data. First, we review the terminology used in the literature and introduce a new nomenclature allowing the unequivocal description of a transfer learning model.
31p guernsey 28-12-2021 3 0 Download
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The Hierarchical Transfer Network (HTN) leverages octave convolution, pyramid features, and self-attention mechanism for revamping the classic models, which can be further integrated with any domain alignment approaches by replacing the feature extractor with the proposed HTN.
13p guernsey 28-12-2021 5 0 Download