The article discusses the development of a deep learning transport emulator to improve air quality forecasting. It is noted that poor air quality negatively impacts human health, and with recent…
Continue readingThe paper proposes a new structure-informed positional encoding framework for music generation with Transformers. The authors note that music generated by deep learning often lacks coherence and long-term organization, which…
Continue readingThe article discusses the development of a new model for speech enhancement called SICRN. The model uses a state space model and inplace convolution techniques to enhance speech quality, especially…
Continue readingThe paper presents a synthetic speech detector called Patched Spectrogram Synthetic Speech Detection Transformer (PS3DT). The detector converts a time domain speech signal to a mel-spectrogram and processes it in…
Continue readingThis paper presents a deep learning method for recognizing Ragas, a significant element in Indian Classical Music (ICM). The method uses Long Short Term Memory based Recurrent Neural Networks (LSTM-RNN)…
Continue readingThis research investigates using ordinal regression methods for categorizing disease severity in chest radiographs. The researchers propose a framework that divides the ordinal regression problem into three parts: a model,…
Continue readingThis research presents an ordinal regression framework for assessing disease severity in chest radiographs using deep learning. The proposed framework divides the ordinal regression problem into three parts: a model,…
Continue readingThe article presents CTGAN (Semantic-guided Conditional Texture Generator), a new method for generating high-quality textures for 3D models. Traditional methods of creating textures can be time-consuming and subjective. CTGAN overcomes…
Continue readingThis academic article presents a comprehensive survey on the use of deep learning methodologies for skill extraction and classification from job postings. The paper addresses the lack of standardized terminology…
Continue readingThe article presents a novel method for time series forecasting, the Sparse Vector Quantized FFN-Free Transformer (Sparse-VQ). This approach leverages sparse vector quantization and Reverse Instance Normalization to reduce noise…
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