- Hybrid convolution neural network model for a quicker detection of ...🔍
- A Hybrid convolution neural network for the classification of tree ...🔍
- A new hybrid model of convolutional neural networks and hidden ...🔍
- Deep Convolution Neural Networks for Automatic Detection of ...🔍
- Quantum classical hybrid convolutional neural networks for breast ...🔍
- Hybrid Optimized Deep Convolution Neural Network based ...🔍
- Hybrid convolution neural network with channel attention ...🔍
- A Hybrid Convolutional Neural Network and Random Forest for ...🔍
Hybrid convolution neural network model for a quicker detection of ...
Hybrid convolution neural network model for a quicker detection of ...
Specifically, while outperforming all other models in terms of accuracy, the proposed hybrid model reduces the training time compared to all models by 16% up to ...
Hybrid convolution neural network model for a quicker detection of ...
In this paper, we propose a hybrid convolution neural network (CNN) model to speed up the detection of fall armyworms (faw) infested maize leaves. Specifically, ...
Hybrid convolution neural network model for a quicker detection of ...
Hybrid convolution neural network model for a quicker detection of infested maize plants with fall armyworms using UAV-based images. Ecological Informatics ...
Hybrid convolution neural network model for a quicker detection of ...
Hybrid convolution neural network model for a quicker detection of infested maize plants with fall armyworms using UAV-based images · List of references.
A Hybrid convolution neural network for the classification of tree ...
Hybrid-CS was trained for tree species classification and included sample sets generated from HJ-1A data. The model makes full use of spectral ...
A new hybrid model of convolutional neural networks and hidden ...
Convolutional neural networks (CNNs) have lately proven to be extremely effective in image recognition. Besides CNN, hidden Markov chains ...
Deep Convolution Neural Networks for Automatic Detection of ...
Fast and accurate defect detection is critical for hybrid bonding because surface defects directly impact yield and processing costs.
Quantum classical hybrid convolutional neural networks for breast ...
explored various convolutional neural network models to aid breast cancer diagnosis. However, classical convolutional neural networks face ...
Hybrid Optimized Deep Convolution Neural Network based ... - arXiv
As a result, the suggested object detection model outperforms other current methods. Comments: 23 Pages, 7 Figures. Subjects: Computer Vision ...
Hybrid convolution neural network with channel attention ...
The convolutional neural network (CNN) model is known for its local connectivity and weight distribution mechanisms, resulting in a reduced ...
A Hybrid Convolutional Neural Network and Random Forest for ...
Forest and land fires are disasters that greatly impact various sectors. Burned area identification is needed to control forest and land ...
A Hybrid Model Combining Convolutional Neural Network with ...
A hybrid model for social media popularity prediction is proposed by combining Convolutional Neural Network (CNN) with XGBoost. The CNN model is exploited ...
(PDF) Hybrid Optimized Deep Convolution Neural Network based ...
suggested object detection model outperforms other current methods. Index terms: Deep Learning, Convolutional Neural Network, ...
A Hybrid Model Based on Convolutional Neural Network and Long ...
The LSTM hyperparameters play an important role in increasing the detection accuracy. The CSA algorithm finds the best values for the ...
Infrared object classification with a hybrid optical convolution neural ...
The proposed system replicates the front convolution layer in a convolutional neural network utilizing a high-speed digital micro-mirror device to display the ...
Robust Boundary Detection From Noisy Images Via Hybrid ... - arXiv
We present CT-Bound, a robust and fast boundary detection method for very noisy images using a hybrid Convolution and Transformer neural network ...
A Hybrid Convolutional Neural Network Model for Diagnosis of ...
COVID-19 declared as a pandemic that has a faster rate of infection and has impacted the lives and the country's economy due to forced lockdowns.
HYBRID‐CNN: An Efficient Scheme for Abnormal Flow Detection in ...
Long Short-Term Memory (LSTM) is a special deep learning model of Recurrent Neural Network. It can remember the input and predicted output ...
A Hybrid Model Composed of Two Convolutional Neural Networks ...
adopted a sliding window (SW)–based CNN combined with graph-search postprocessing for automatic identification of retinal layer boundaries in OCT images of dry ...
Fast Hybrid Deep Neural Network for Diagnosis of COVID-19 using ...
They utilized five pre-trained CNN-based models: ResNet152,. ResNet101, ResNet50, Inception-ResNetV2, and InceptionV3. The highest classification accuracy was ...