Accurately identifying defect patterns in wafer maps can help engineers find abnormal failure factors in production *** the wafer testing stage,deep learning methods are widely used in wafer defect detection due to th...
详细信息
Accurately identifying defect patterns in wafer maps can help engineers find abnormal failure factors in production *** the wafer testing stage,deep learning methods are widely used in wafer defect detection due to their powerful feature extraction ***,most of the current wafer defect patterns classification models have high complexity and slow detection speed,which are difficult to apply in the actual wafer production *** addition,there is a data imbalance in the wafer dataset that seriously affects the training results of the *** reduce the complexity of the deep model without affecting the wafer feature expression,this paper adjusts the structure of the dense block in the PeleeNet network and proposes a lightweight network WM‐PeleeNet based on the PeleeNet *** addition,to reduce the impact of data imbalance on model training,this paper proposes a wafer data augmentation method based on a convolutional autoencoder by adding random Gaussian noise to the hidden *** method proposed in this paper has an average accuracy of 95.4%on the WM‐811K wafer dataset with only 173.643 KB of the parameters and 316.194 M of FLOPs,and takes only 22.99 s to detect 1000 wafer *** with the original PeleeNet network without optimization,the number of parameters and FLOPs are reduced by 92.68%and 58.85%,*** augmentation on the minority class wafer map improves the average classification accuracy by 1.8%on the WM‐811K *** the same time,the recognition accuracy of minority classes such as Scratch pattern and Donut pattern are significantly improved.
Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread ***,few works have been...
详细信息
Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread ***,few works have been payed on the estimation of the two degra-dation *** learn the two functions from image pairs to be fused,we propose a Dirichletnetwork,where both functions are properly ***,the spatial response function isconstrained with positivity,while the Dirichlet distribution along with a total variation is imposedon the point spread *** the best of our knowledge,the neural network and the Dirichlet regularization are exclusively investigated,for the first time,to estimate the degradation *** image degradation and fusion experiments demonstrate the effectiveness and superiority of theproposed Dirichlet network.
A hybrid diffuse optical monitoring device was developed using multi-wavelength lasers for both diffuse correlation spectroscopy (DCS) and diffuse optical spectroscopy (DOS). In-vivo experiments have validated the pro...
详细信息
The limited resolution of cameras and the wide field of the video surveillance systems lead to low quality captured facial images and difficult to identify. Face super-resolution methods are proposed to enhance the re...
详细信息
Due to the lack of infrared image data, infrared target detection is still a challenging task. To increase the performance of infrared target detection, this paper proposes a feature distillation method based on dual ...
详细信息
Efficient and collision-free coordination of two robot arms is increasingly needed in various service-oriented robotic applications. This paper proposes a dual-arm coordination algorithm to improve the efficiency of c...
详细信息
As it is difficult to get an accurate mathematical noise model under various dynamic interference conditions,Strap-down Inertial Navigation system(SINS) was difficult to realize *** the fuzzy adaptive Kalman filter ca...
详细信息
ISBN:
(纸本)9781467383196
As it is difficult to get an accurate mathematical noise model under various dynamic interference conditions,Strap-down Inertial Navigation system(SINS) was difficult to realize *** the fuzzy adaptive Kalman filter can be used to realize the SINS self-alignment,the algorithm complexity is high and the error term is *** solve this problem,a novel self-alignment method using real-time adaptive filter was developed in this *** method is based on the theory of fuzzy adaptive adjustment and used the filter stability as the *** exponential function was used to replace the fuzzy inference calculation,which eliminated the complex process of fuzzy,fuzzy inference and *** stability and accuracy of the adaptive filter was also ***,the simulation process was used to test the algorithm of this method,and the results demonstrated that the self-alignment using real-time adaptive filter method reduced the complexity of the algorithm and had better stability and alignment accuracy.
Wafer bin map(WBM)inspection is a critical approach for evaluating the semiconductor manufacturing *** excellent inspection algorithm can improve the production efficiency and *** paper proposes a WBM defect pattern i...
详细信息
Wafer bin map(WBM)inspection is a critical approach for evaluating the semiconductor manufacturing *** excellent inspection algorithm can improve the production efficiency and *** paper proposes a WBM defect pattern inspection strategy based on the DenseNet deep learning model,the structure and training loss function are improved according to the characteristics of the *** addition,a constrained mean filtering algorithm is proposed to filter the noise *** model prediction,an entropy-based Monte Carlo dropout algorithm is employed to quantify the uncertainty of the model *** experimental results show that the recognition ability of the improved DenseNet is better than that of traditional algorithms in terms of typical WBM defect *** the model uncertainty can not only effectively reduce the miss or false detection rate but also help to identify new patterns.
Manually designed deep neural networks have successfully forwarded waste recognition tasks in the resource recycling field. However, due to the diversity of waste samples, the feature extraction ability of inherently ...
详细信息
The challenge in image-based visual servoing is to deal with the visibility constraints, which require the image features to always remain in the field of view (FOV) of the camera. In this paper, a novel constraint fu...
详细信息
暂无评论