Abstract: Convolutional Neural Networks (CNNs) have shown significant success in the low-light image enhancement task. However, most of existing works encounter challenges in balancing quality and ...

Abstract: Ultrasound imaging is widely used in clinical practice due to its advantages of no radiation and real-time capability. However, its image quality is often degraded by speckle noise, low ...

Abstract: Coronary Heart Disease popularly referred to as CHD is one of the leading causes of death and illness across the global population making it imperative for the identification of an effective ...

Abstract: Aiming at the problem that most thermal error prediction models for machine tools adopt a single neural network architecture, which is difficult to ...

Abstract: Human cognition is robust in estimating depth ordering and occluded regions of objects, including amodal instance segmentation (AIS). Object-centric representation learning (OCRL) is an ...

Abstract: An accurate land-cover segmentation of very-high-resolution aerial images is essential for a wide range of applications, including urban planning and natural resource management. However, ...

Abstract: Audio is vital information data for understanding various situations. A multitude of sound features can be explained by analysis through the audio signals. Numerous classification methods ...

Abstract: The grading of fruits relies on inspections, experiences, and observations, with a proposed system integrating machine learning techniques to assess fruit freshness. By analyzing 2D fruit ...

Abstract: Efficient image compression is crucial for remote sensing (RS) satellite systems, as it determines the performance of machine vision applications analyzing the downlinked image data at ...

Abstract: ’Fake news’ refers to false, inaccurate, or misleading information that spreads as real news. Fake news primarily aims to affect societies and individuals by spreading false or misleading ...