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Automatic DenseNet Sparsification [PDF]
IEEE Access, 2020 As a classic and well-performed deep convolutional neural network, DenseNet links every layer to each of its preceding layers via skip connections. However, the dense connectivity of the links leads to much redundance, consuming lots of computational ...
Tao Li, Wencong Jiao, Li-Na Wang
exaly +4 more sources
S-DenseNet: A DenseNet Compression Model Based on Convolution Grouping Strategy Using Skyline Method [PDF]
IEEE Access, 2019 DenseNet has strong expressiveness in many computer vision tasks, but the complexity of its model makes it difficult to deploy to devices with limited computing resources.
Changyong Yu, Xin He, Haitao
exaly +4 more sources
Multiple Feature Reweight DenseNet for Image Classification
IEEE Access, 2019 Recent network research has demonstrated that the performance of convolutional neural networks can be improved by introducing a learning block that captures spatial correlations.
Ke Zhang
exaly +3 more sources
Assessment of Pain Intensity Using Deep Learning Models in Non-Communicative Intensive Care Patients. [PDF]
Nurs Crit CareABSTRACT Background Pain is a multifaceted and subjective phenomenon frequently experienced by patients in intensive care units. In non‐communicating populations, conventional assessment tools are often inadequate and susceptible to observer bias. Deep learning‐based facial analysis has emerged as a promising approach for the objective quantification ...
Guven S, Aslan FE, Canayaz M.
europepmc +2 more sources
Effective Combination of DenseNet and BiLSTM for Keyword Spotting
IEEE Access, 2019 Keyword spotting (KWS) is a major component of human-computer interaction for smart on-device terminals and service robots, the purpose of which is to maximize the detection accuracy while keeping footprint size small.
Mengjun Zeng, Nanfeng Xiao
exaly +3 more sources
Disease Detection in Banana Leaf Plants using DenseNet and Inception Method
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022 Diseases that attack banana plants can affect the growth and productivity of the fruit produced. The disease can be identified by looking at changes in the pattern and color of the leaves.
Andreanov Ridhovan +2 more
doaj +1 more source
DenseNet-DC: Optimizing DenseNet Parameters Through Feature Map Generation Control [PDF]
Revista de Informática Teórica e Aplicada, 2020 Convolutional Neural Networks still suffer from the need for great computational power, oftenrestricting their use on various platforms. Therefore, we propose a new optimization method made for DenseNet, a convolutional neural network that has the characteristic of being completely connected.
Andre Tavares da Silva +1 more
openaire +2 more sources
Frontiers in Bioscience-Landmark, 2023 Background: 5-methylcytosine (m5C) is a key post-transcriptional modification that plays a critical role in RNA metabolism. Owing to the large increase in identified m5C modification sites in organisms, their epigenetic roles are becoming increasingly ...
Jianhua Jia, Lulu Qin, Rufeng Lei
doaj +1 more source
comparison of small sample methods for Handshape Recognition
Journal of Computer Science and Technology, 2023 Automatic Sign Language Translation (SLT) systems can be a great asset to improve the communication with and within deaf communities. Currently, the main issue preventing effective translation models lays in the low availability of labelled data, which ...
Franco Ronchetti +6 more
doaj +1 more source
Application with deep learning models for COVID-19 diagnosis
Sakarya University Journal of Computer and Information Sciences, 2022 COVID-19 is a deadly virus that first appeared in late 2019 and spread rapidly around the world. Understanding and classifying computed tomography images (CT) is extremely important for the diagnosis of COVID-19.
Yunus Kökver, Fuat Türk
doaj +1 more source