Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 600 for “"CNN)"”.
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Speech enhancement using deep dilated CNN
In recent years, deep learning has achieved great success in speech enhancement. However, there are two major limitations regarding existing works. First, the Bayesian framework is not adopted in many such deep-learning-based algorithms. In particular, the prior distribution for speech in the …
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PFHE: partially homomorphic encryption on CNN inference
… encrypted Convolutional Neural Network (CNN) inference by only encrypting the privacy-sensitive regions of input while processing the remaining parts in plaintext. Our method significantly reduces computational cost without compromising data confidentiality. We developed a new data layout …
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Deep CNN-Based Automated Optical Inspection for Aerospace Components
… are employed for both datasets. Second, deep CNN-based models, such as improved ResNet50 and MobileNetV2 architectures are trained on ACMID datasets. Third, an efficient defect detection technique that combines the features of deep learning and classical machine learning model is proposed for …
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Application of CNN-gcForestCS to cassava leaf image classification
… systems using convolutional neural networks (CNNs) deployable on mobile phones have shown to be a cost-efficient and effective method for cassava monitoring, mainly owing to their advanced feature extraction capabilities. However, CNNs require complex hyperparameter tuning and can be …
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All Analog CNN Accelerator with RRAMs for Fast Inference
… analysis on a convolutional neural network (CNN) accelerator that implements such a system, optimizing for inference speed. The accelerator duplicates all of the computation hardware, thus eliminating the need to fetch data back and forth while reusing the same hardware. We propose a novel …
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DGCNN : learning point cloud representations by dynamic graph CNN
… success of convolutional neural networks (CNNs) for image analysis suggests the value of adapting insight from CNN to the point cloud world. Point clouds inherently lack topological information so designing a model to recover topology can enrich the representation power of point clouds. To …
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NN2FPGA: Optimizing CNN Inference on FPGAs with Binary Integer Programming
L'abstract è presente nell'allegato / the abstract is in the attachment
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Internet CNN Newsroom : the design of a digital video news magazine
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
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An Energy-Efficient Spiking CNN Implementation for Cross-Patient Epileptic Seizure Detection
… then sent into a convolutional neural network (CNN) as inputs. Our convolutional neural network as a deep learning method learns a general spatially irreducible representation of a seizure to improves sensitivity, specificity, and accuracy results comparable to the state-of-the-art results. In …
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Apprendimento di modelli per reti cellulari non lineari (CNN): tecniche e applicazioni
… del modello per le reti neurali cellulari (CNN) applicati a varie attività di elaborazione delle immagini. Attraverso l'apprendimento supervisionato, oppure tramite l'elaborazione delle immagini tecniche o schizzi manuali, l'algoritmo RWC ha ridotto al minimo l'errore con successo tra le …
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Evaluating deep learning for enhanced breast cancer diagnosis: a comparative analysis of CNN architectures
… particularly convolutional neural networks (CNNs), in breast cancer subtype classification using histology images. A custom CNN model, alongside well-established models like ResNet50 and EfficientNetB0, was developed and evaluated for its accuracy in predicting benign and malignant breast …
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G A N mask R-CNN : instance semantic segmentation benefits from generative adversarial networks
… the true distribution, and a ConvNet like Mask R-CNN is an implicit model that infers the true distribution. In GANs terms, Mask R-CNN is the generator who reconstructs a mask as the fake one. We then send the fake mask and the real (ground truth) one to a discriminator (critic). By playing a …
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User adaptation of a networked technology : internet CNN Newsroom in a high school classroom
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.
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High-Resolution Additive Manufacturing Error Prediction and Compensation Through 3D CNN Leveraging Semantic Segmentation
Additive manufacturing (AM) is a relatively new domain of manufacturing processes that began with its first patent in 1986. Since then, AM processes quickly grew in popularity due to their flexibility, superior efficiency in high mix low volume manufacturing settings, and lower material costs …
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Measuring and comparing the readability and vocabulary coverage of CNN, China Post and Taipei Times
… coverage, vocabulary levels and readability of CNN, the China Post and the Taipei Times. It is hoped that this study could provide a more effective and cost-benefit way to assist teachers in choosing suitable texts for vocabulary learning and for reading instruction. It could also offer some …
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