cnn-icp-softmax (SoftMax Inc)
90
Structured Review
SoftMax Inc
cnn-icp-softmax
Cnn Icp Softmax, supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/normalized+exponential+function+(softmax)+module+804/cnn+softmax/pmc11211563-167-8-9
Average 90 stars, based on 1 article reviews
Cnn Icp Softmax, supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/normalized+exponential+function+(softmax)+module+804/cnn+softmax/pmc11211563-167-8-9
Average 90 stars, based on 1 article reviews
cnn-icp-softmax - by Bioz Stars,
2026-09
90/100 stars
Images
1) Product Images from "Recent advancements in machine learning for bone marrow cell morphology analysis"
Article Title: Recent advancements in machine learning for bone marrow cell morphology analysis
Journal: Frontiers in Medicine
doi: 10.3389/fmed.2024.1402768
Figure Legend Snippet: A summary of examples of BMC classification automation.
Techniques Used: Selection, Construct, Diagnostic Assay, Imaging
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[46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Biomarker Discovery:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Extraction:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Selection:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Imaging:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Plasmid Preparation:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Derivative Assay:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Microscopy:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Staining:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Diagnostic Assay:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Control:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% Generated:Article Title: Fusion‐Brain‐Net: A Novel Deep Fusion Model for Brain Tumor Classification Article Snippet: Subba and Sunaniya ( ) , Figshare , Article Title: Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis Article Snippet: Sakthiraj ( ) , Hybrid Convolutional Neural Network with Interactive Autodidactic School (HCNN-IAS) algorithm , HCNN-IASO , No , Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment. Article Snippet: Gong et al. [46] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Recognition of Drill String Vibration State Based on WGAN-div and CNN-IWPSO-SVM Article Snippet: During drilling operations, complex and variable dynamic nonlinear loads result in intricate vibrations in the drill string, severely impacting drilling safety and efficiency.. The vibration data collected on-site contains rich information about vibration conditions.. Addressing the limitations of existing signal processing methods in vibration state monitoring, this study proposes a hybrid method combining deep learning and machine learning for vibration state classification. Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification Article Snippet: , 91% , , Article Title: Deep learning based gasket fault detection: a CNN approach. Article Snippet: Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved Article Title: Fault Diagnosis Method of Rolling Bearing Based on 1D Multi-Channel Improved Convolutional Neural Network in Noisy Environment Article Snippet: Gong et al. [ ] proposed an improved Convolutional Neural Network Support Vector Machine, which can directly input the original data from multiple sensors into the Article Title: Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification. Article Snippet: The Methods BreakHis dataset Classification type Classification methodOptimal accuracy ICIAR dataset 41 91.38% Binary class VLAD 42 93.3% Binary class K-mean + DWT 43 86.67% Binary class Fisher Vector + CNN 44 91% |