... and the complexity of multimodal data used for patient status depiction. In this work, the authors develop an end-to-end deep learning ( DL ) framework that incorporates multimodal patient data and multiple treatments for accurate ITE inference in a retrospective head and neck cancer ( HNC ) study. A possible...

... approaches. SISR models: SISR is a classic vision task that aims to reconstruct an HR image from a given LR image. The introduction of deep learning-based approaches, which do not rely on carefully selected prior knowledge, has significantly advanced the field. Initially, shallow...

...-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at Link to the terms of the CC BY 4.0 license. Deep learning Assisted diagnosis Cervical lesions Transformer Innovation of Science and Technology, Fujian...

... of this licence may be seen at Link to the terms of the CC BY 4.0 licence Deep learning Speech enhancement Zero-shot National Science and Technology Council of Taiwan 111-2221-E-006-150-MY3 This work was supported in part by the National Science and Technology Council of Taiwan, under...

... images obtained by conventional CT reconstruction techniques exhibit noises and streak artifacts. Deep learning techniques are changing this situation. However, there are few reviews that recently focus on the fast developing area. This paper reviews recent research on CT reconstruction of incomplete...

... of this licence may be seen at Link to the terms of the CC BY-NC 4.0 licence . Epilepsy electroencephalogram (EEG) seizure deep learning EEGWaveNet Epilepsy is a group of neurological disorders, characterized by unprovoked and recurrent seizures in a patient over a certain period [ 11...

...-BiLSTM are Deep Learning (DL) models to assess the ASVspoof on the ASVspoof2021 datasets. DL entails the process of transforming manually crafted feature vectors (FVs) into more extensive, dense FVs via matrix multiplication. A DL model’s architecture may be modified to fit...

...Ryotaro Nagase; Takahiro Fukumori; Yoichi Yamashita Recently, much research has been actively conducted on speech emotion recognition (SER) using deep learning, which predicts emotions conveyed by speech. Our study focused on a method of recognizing emotions at each frame level. One challenge...

... of this licence may be seen at Link to the terms of the CC BY-NC 4.0 licence . Diff-quick cell images microscopic cell segmentation automatic deep learning DiffQuick is a rapid, cost-effective staining protocol that colors nuclei and cytoplasm differently. It is indispensable for routine...

... publication and authors. The full terms of this licence may be seen at Link to the terms of the CC BY-NC 4.0 licence . Point Cloud Compression 3D Object Detection Deep learning In autonomous driving, point cloud is a crucial 3D data format that comprises a series of dispersed, unordered...

...Tian Yang; Xinhui Yu; Martin J. McKeown; Z. Jane Wang Deep learning has been a powerful tool for medical image analysis, but large amount of high-quality labeled datasets are generally required to train deep learning models with satisfactory performance and generalization capability. In medical...

... in deep learning technology, FSR methods using deep learning have achieved notable subjective and objective reconstruction quality, attracting extensive industrial attention. However, detailed classifications of FSR methods remain limited. Therefore, this survey systematically and comprehensively reviews...

... and cannot be repeated for every tone mapped image. To address this issue, numerous quantitative metrics have been proposed for objective evaluation. This paper presents a robust objective metric based on deep learning to quantify image quality. We assess the performance of our proposed metric by comparing...

... to the original publication and authors. The full terms of this licence may be seen at Link to the terms of the CC BY-NC 4.0 licence. Medical report generation deep learning artificial intelligence review Automatic medical report generation (AMRG) is an emerging research area in artificial...

...-commercial purposes only), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at Link to the terms of the CC BY-NC 4.0 licence. SAR images ship detection coordinate system projection deep learning SAR systems have unique...

... to the original publication and authors. The full terms of this licence may be seen at Link to the terms of the CC BY-NC 4.0 licence . Medical Artificial Intelligence Deep Learning Computer Vision Natural Language Processing Healthcare In recent years, the application of artificial intelligence...

... to segment real-world features and match them for authentication. It presents a case study of a new model based on the Siamese neural network. It explains how the Siamese neural network can be used for biometric recognition and how it compares to other deep learning models commonly used in the field. Lastly...

...Yakun Yang; Anhong Wang; Songyu Zhai Point cloud upsampling can provide a dense and uniform representation, which is crucial for improving the quality of 3D reconstruction. While many traditional and deep learning methods of point cloud upsampling have been proposed, their performance need...

...Kanghao Zhang; Shulin He; Hao Li; Xueliang Zhang Single-channel speech enhancement aims to remove the interfering noise and reverberation in real environments by a single microphone, which is a very challenging task in the speech signal processing field. Over the past years, deep learning has shown...

... taking place in the video, has been widely applied in many applications. This paper presents a comprehensive survey of approaches and techniques in deep learning-based human activity analysis. First, we introduce the problem definition in action recognition together with its challenges. Second, we...