Inception-v4, inception-resnet and the impact of residual connections on learning
… With an ensemble of three residual and one Inception-v4 networks, we achieve 3.08% top-5 …
For that purpose, we evaluated a new version named Inceptionv4 which has a more uniform …
For that purpose, we evaluated a new version named Inceptionv4 which has a more uniform …
Feature fusion and kernel selective in Inception-v4 network
F Chen, J Wei, B Xue, M Zhang - Applied Soft Computing, 2022 - Elsevier
… on the Inception-v4 model and has made several improvements. The improved Inception-v4 …
Kernel Network (SKNet) into the Inception-v4 network, and adjusts the network structure to …
Kernel Network (SKNet) into the Inception-v4 network, and adjusts the network structure to …
Thermal-based early breast cancer detection using inception V3, inception V4 and modified inception MV4
… neural networks modelling inception V3, inception V4, and a modified … The training results
showed that inception V4 and MV4 with … is almost comparable to inception V4 and MV4 (color) …
showed that inception V4 and MV4 with … is almost comparable to inception V4 and MV4 (color) …
A modified inception-v4 for imbalanced skin cancer classification dataset
… Modified Inception-v4 We extend the design of inception-v4 but add a residual connection
to … The modified inception-v4 architecture is shown in figure 1 and consists of the following …
to … The modified inception-v4 architecture is shown in figure 1 and consists of the following …
[PDF][PDF] Audio Bird Classification with Inception-v4 extended with Time and Time-Frequency Attention Mechanisms.
A Sevilla, H Glotin - CLEF (Working Notes), 2017 - scholar.archive.org
… We present an adaptation of the deep convolutional network Inception-v4 tailored to solving
bioacoustic classification problems. Bird sound classification was treated as if it were an …
bioacoustic classification problems. Bird sound classification was treated as if it were an …
A Novel CNN‐Inception‐V4‐Based Hybrid Approach for Classification of Breast Cancer in Mammogram Images
… So, using the CBIS-DDSM (Curated Breast Imaging Subset of DDSM) dataset [27], this
research provides a novel hybrid approach CNN-Inception-V4 for classifying breast cancer as …
research provides a novel hybrid approach CNN-Inception-V4 for classifying breast cancer as …
Grading and fraud detection of saffron via learning-to-augment incorporated Inception-v4 CNN
… According to the regular CNN-based model detailed in Table 4, Configuration 1 of the model
without using the Inception-v4 technique in CNN contains of 6 convolution layers, 6 ReLU …
without using the Inception-v4 technique in CNN contains of 6 convolution layers, 6 ReLU …
Comparison between ResNet 16 and inception V4 network for COVID-19 prediction
PJ Rachana, A Kodipalli, T Rao - Emerging Research in Computing …, 2022 - Springer
… This paper proposes a new deep learning architecture inception v4 to automatically detect
COVID-19 using the chart X-ray images. The proposed methodology provided improved …
COVID-19 using the chart X-ray images. The proposed methodology provided improved …
Improved AlexNet with Inception‐V4 for Plant Disease Diagnosis
Z Li, C Li, L Deng, Y Fan, X Xiao, H Ma… - Computational …, 2022 - Wiley Online Library
… In this paper, the AlexNet structure is combined with the inception-V4 structure to take
both cons of those two structures. The Inception-V4 module is added based on the AlexNet …
both cons of those two structures. The Inception-V4 module is added based on the AlexNet …
XGBoost regression classifier (XRC) model for cyber attack detection and classification using inception V4
KMK Raghunath, VV Kumar… - Journal of Web …, 2022 - ieeexplore.ieee.org
… Evaluation of the performance of the proposed XRC model integrated with inception V4
was discussed in this section. The performance measures that will be analysed are specified. …
was discussed in this section. The performance measures that will be analysed are specified. …