Evaluated design choices in Convolutional Neural Network
Iris Recognition using Convolutional Neural Network Design
... The optimization techniques have shown slightly varying recognition rates for same data base. This is due to hyper parameter selection. However it is to be noted that for RMSprop optimization the recognition rates are ...
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Energy-efficient Hardware Accelerator Design for Convolutional Neural Network
... During the process of reading and writing the partial sum, it is rounded and this process generates an additional error, named channel loop tiling-error. Because channel loop tiling-error deteriorates CNN accuracy, it ...
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Design of Hardware Accelerators for Hierarchical Temporal Memory and Convolutional Neural Network.
... proposed design, we count the target segment activity by counting the number of matching pairs between the cells in current active list and those stored in target ...
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Improving Convolutional Neural Network Design via Variable Neighborhood Search
... stores the output size of each layer, allowing to assess the validity of the network architecture. The second column of S defines the size of the filters of C (3, 5, 7 or 9 in our experiments) and MP layers (2, 3, ...
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Fixed layer Convolutional Neural Network
... The ROC curve shows how well a binary classifier can distinguish between the two choices. In a classifier there will always be false positives and false negatives. A threshold needs to be decided on, in order to ...
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Convolutional Neural Network Language Models
... a convolutional architecture for sentence repre- sentation that vertically stacks multiple convolution layers, each of which can learn independent convo- lution ...only evaluated through downstream tasks ...
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Design And Development Of A License Plate Recognition System Using Convolutional Neural Network
... viii ABSTRAK Kenderaan di jalan raya telah meningkat secara mendadak dalam dekad ini. Oleh itu, pelaksanaan sistem pengecaman nombor plat kenderaan amat diperlukan untuk mengawal dan pengawasan terhadap aliran trafik. ...
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Garments Texture Design Class Identification Using Deep Convolutional Neural Network
... Garments Texture Design Class Identification Using Deep Convolutional Neural Network.. S.M.[r] ...
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19 Better Neural Network Training; Convolutional Neural Networks
... A bigger problem with having billions of weights is that the network becomes very slow to train or even to use.] [Researchers have addressed these problems by taking inspiration from the neurology of the visual ...
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Waste Segregation using Convolutional Neural Network
... [2] Shanjenbam Brojendro Singh, Abu Salah Muslaha Uddin Laskar, Biltu Roy, Aminul Hoque Choudhury, Zahidul Islam, Jakir Hussain Mollah, Shadeed Masood Hoque, Mohsin Ali, Pranav Kalita, "Design of Municipal Dry ...
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A Convolutional Neural Network Cascade for Face Detection
... Figure 8: Manually curated detection bounding boxes on AFW: blue boxes are faces mis-evaluated to be false alarms; green boxes are unannotated faces. These are all detections our approach generated but ...
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Rethinking the Pruning Criteria for Convolutional Neural Network
... these two conditions do not always hold, a new criterion considering the relative Importance Score of the filters is proposed [4]. Since this criterion uses the Fermat point (i.e., geometric median [14]), we call this ...
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Convolutional neural network-based place recognition
... Place recognition is essentially a task of image similarity matching. In [Fischer, et al., 2014], features from various layers of CNNs are evaluated and compared with SIFT descriptors on a descriptor matching ...
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Gender classification: a convolutional neural network approach
... a convolutional neural network (CNN) is proposed for real-time gender classification based on facial ...reduced design complexity when compared with other CNN solutions applied in pattern ...
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DNA Sequence Classification by Convolutional Neural Network
... called convolutional neural network with an ability of ex- tracting features of high-level abstraction from minimum preprocessing data has been widely ...volutional neural network while ...
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Image Segmentation Using Convolutional Neural Network
... 2.5.3 Activation Layer This layer mostly uses ReLu as an activation function. ReLu is a function which is used to set all negative values to zero and keeps positive value as it is. This step is usually followed by ...
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An Improved Retraining Scheme for Convolutional Neural Network
... Although CNN has improved the performance of MLP, the complexity of its structure has caused retraining processes to become inefficient whenever new categories or neurons using a winner-takes-all approach are added at ...
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A Multithreaded CGRA for Convolutional Neural Network Processing
... with official libraries [3] both in academic/busuiness purposes. 7. Conclusion We proposed a CGRA architecture with time-domain multithreading for ex- ploiting input data locality. This architecture employs the ...
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3D Convolutional Neural Network for Object Recognition
... VI. CONCLUSION The paper describes the recognition task on 3D data using voxel based 3D data representation. The performance of CNN on different size of voxels has been analyzed. The analysis further motivated to ...
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A Detection algorithm based on Convolutional Neural Network
... we design a station logo detection method based on Convolutional Neural Network by the characteristics of the station, such as small scale-to-height ratio change and relatively fixed ...
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