Existing end-to-end speech recognition methods typically employ hybrid decoders based on CTC and Transformer. However, the issue of error accumulation in these hybrid decoders hinders further improvements in accuracy. Additionally, most existing models are built upon Transformer architecture, which tends to be complex and unfriendly to small datasets.
View Article and Find Full Text PDFCamouflaged object detection (COD) aims to segment those camouflaged objects that blend perfectly into their surroundings. Due to the low boundary contrast between camouflaged objects and their surroundings, their detection poses a significant challenge. Despite the numerous excellent camouflaged object detection methods developed in recent years, issues such as boundary refinement and multi-level feature extraction and fusion still need further exploration.
View Article and Find Full Text PDFVisual navigation involves a movable robotic agent striving to reach a point goal (target location) using vision sensory input. While navigation with ideal visibility has seen plenty of success, it becomes challenging in suboptimal visual conditions like poor illumination, where traditional approaches suffer from severe performance degradation. We propose E3VN (echo-enhanced embodied visual navigation) to effectively perceive the surroundings even under poor visibility to mitigate this problem.
View Article and Find Full Text PDFIn this work, graphene oxide@Fe3O4 (GO@Fe3O4) two-dimensional magnetically oriented nanocomposites were prepared through the co-precipitation approach using graphene oxide as the carrier and FeCl3·6H2O and FeSO4·7H2O as iron sources. The samples were characterized and tested by X-ray diffraction, a transmission electron microscope, Fourier-transform infrared spectroscopy, a vibrating-specimen magnetometer, a polarized optical microscope, an optical microscope, etc. The effects of material ratios and reaction conditions on the coating effects of Fe3O4 on the GO surface were investigated.
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