Abstract: The Convolutional Neural Network (CNN) is a frequently used algorithm used technique ... types of sparse data obtained via distinct pruning procedures. The design architecture outlined in ...

Abstract: In this paper, we propose a highly efficient VLSI architecture for context-based adaptive variable-length coding (CAVLC) decoder. In multimedia data processing systems, the real-time ...

With the use of this dataset, we trained a bespoke Convolutional Neural Network (CNN) model, yielding testing, validation, and training accuracies of 89.50%, 92.53%, and 89.58%, respectively.

This approach leads to efficient utilization of FPGA hardware resources while computing all layers in the CNN. The proposed architecture shows performance improvement in the range of $1.4\times $ to ...

This paper introduces a compact end-to-end multi-branch convolutional neural network (CNN) architecture designed to decode brain signals from diverse modalities. The model integrates designated ...

Abstract: Scaling up Artificial Intelligence (AI) algorithms for massive datasets to improve their performance is becoming crucial. In Machine Translation (MT), one of most important research fields ...

In this paper, we propose a waste segmentation method using Convolutional Neural Network based on the Encoder-Decoder approach of SegNet architecture [5]. We compare two different setups of the ...

Abstract: The breast cancer based image classification and division is proposed by utilizing a Deep learning (DL) technique. A few DL models is used to classify Mammographic information to forecast ...

Inspired by the powerful global modelling capability of Swin Transformer, we propose the LSENet network, which follows the encoder-decoder architecture of the UNet network. In encoding phase, we ...

To address the aforementioned limitations, this article proposes a multisource data fusion classification method based on a cross-modal cascaded encoder-decoder network (CCEnd-Net). The proposed ...

Abstract: Designers are increasingly trust on field programmable gate array (FPGA) based emulation to evaluate the performance of Convolutional Encoder. Optimization of XOR operators is the very ...