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Found 8 papers, 0 papers with code
Robust Clustering using Hyperdimensional Computing
To overcome this bottleneck, we assign the initial cluster hypervectors by exploring the similarity of the encoded data, referred to as \textit{query} hypervectors.
Tensor Decomposition for Model Reduction in Neural Networks: A Review
Modern neural networks have revolutionized the fields of computer vision (CV) and Natural Language Processing (NLP).
Multi-Channel FFT Architectures Designed via Folding and Interleaving
Computing the FFT of a single channel is well understood in the literature.
LayerPipe: Accelerating Deep Neural Network Training by Intra-Layer and Inter-Layer Gradient Pipelining and Multiprocessor Scheduling
The proposed system, referred to as LayerPipe, reduces the number of clock cycles required for training while maximizing processor utilization with minimal inter-processor communication overhead.
Teaching Digital Signal Processing by Partial Flipping, Active Learning and Visualization
Effectiveness of teaching digital signal processing can be enhanced by reducing lecture time devoted to theory, and increasing emphasis on applications, programming aspects, visualization and intuitive understanding.
PERMDNN: Efficient Compressed DNN Architecture with Permuted Diagonal Matrices
On the other hand, the recent structured matrix-based approach (i. e., CirCNN) is limited by the relatively complex arithmetic computation (i. e., FFT), less flexible compression ratio, and its inability to fully utilize input sparsity.
Classification using Hyperdimensional Computing: A Review
Additionally, due to the nature of those three operations, HD computing leads to fast learning ability, high energy efficiency and acceptable accuracy in learning and classification tasks.
Automated OCT Segmentation for Images with DME
For estimating the sub-retinal layer thicknesses, the proposed system has an average error of 0. 2-2. 5 $\mu m$ and 1. 8-18 $\mu m$ in normal and abnormal images, respectively.
