Richard Jiang

TL;DR: A review of the state-of-the-art in relation to explainability of artificial intelligence in the context of recent advances in machine learning and deep learning can be found in this paper.

TL;DR: An new approach Many Graph Embedding (MGE) to discover discriminative patterns from the subspaces of chaotic patterns, where the facial expression recognition is carried out as a fuzzy combination from many graph embedding, making the method a promising candidate for the scrambled face expression recognition in the emerging privacy-protected IoT applications.

TL;DR: A novel high-performance 8k-point fast Fourier transform (DFT) processor architecture for OFDM digital video broadcasting (DVB) is proposed based on a novel radix-8 FFT architecture, which can greatly save the area cost while keeping a high-speed processing speed.

TL;DR: The results show that the proposed scheme can attain better accuracy in comparison with the conventional multimodal fusion using latent semantic analysis as well as the single-modality verifications.

TL;DR: The proposed PQIS-Net model is aimed at providing fully automated segmentation of lung CT slices without incorporating pre-trained convolutional neural network based models, and is found to be superior than the best state-of-the-art techniques and pre- trained convolutionAL neural network-based models, specially in COVID-19 and Mycoplasma Pneumonia screening.