Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition

Online handwritten Chinese text recognition (OHCTR) is a challenging problem as it involves a large-scale character set, ambiguous segmentation, and variable-length input sequences. In this paper, we exploit the outstanding capability of path signature to translate online pen-tip trajectories into informative signature feature maps using a sliding window-based method, successfully capturing the analytic and geometric properties of pen strokes with strong local invariance and robustness. A multi-spatial-context fully convolutional recurrent network (MCFCRN) is proposed to exploit the multiple spatial contexts from the signature feature maps and generate a prediction sequence while completely avoiding the difficult segmentation problem. Furthermore, an implicit language model is developed to make predictions based on semantic context within a predicting feature sequence, providing a new perspective for incorporating lexicon constraints and prior knowledge about a certain language in the recognition procedure. Experiments on two standard benchmarks, Dataset-CASIA and Dataset-ICDAR, yielded outstanding results, with correct rates of 97.10% and 97.15%, respectively, which are significantly better than the best result reported thus far in the literature.Comment: 14 pages, 9 figure

Lithofacies, mineralogy, and pore characteristics of Permian marine tuffaceous rocks in the Sichuan Basin

Alongside volcanic eruptions in the middle and late Permian, the sedimentary environment and process changed, and the lithofacies and mineralogical characteristics varied conspicuously from the marine sediments in this period. Marine tuffaceous rocks beared strong witness to the marine and volcanic actions in this time. With experimental studies relying on field outcrop, thin section, scanning electron microscope, X-ray diffraction (XRD), mercury injection capillary pressure (MICP) and CT scan, the researchers analyzed the lithology, mineralogy, and pore characteristics of marine tuffaceous rocks. Among the Permian marine tuffaceous sections of the Sichuan Basin, three types of lithofacies were identified, namely tuff, sedimentary tuff, and tuffaceous mudstone. The mineral composition of the tuffaceous section includes quartz, feldspar, carbonate minerals, pyrite, clay, etc. The quartz content varies from 4.0% to 27.3%, with an average value of 13.0%; the feldspar content varies from 0 to 21.2%, with an average value of 9.8%; the carbonate mineral content varies from 8.52% to 53.45%, with an average value of 27.6%; the clay mineral content varies from 0 to 75.3%, with an average value of 44.8%; and the pyrite content varies from 0 to 13.4%, with an average value of 5.8%. The porosity of tuffaceous rocks varies from 2.2% to 8.1%, mostly concentrated in the range from 3% to 7% with an average level of 5.24%. There are mainly shrinkage pores, dissolution pores, intercrystalline pores, and organic pores. In terms of scale, the pores can be classified as micron-scale and nano-scale pores, and in terms of size, they are mainly micropores and mesopores, accounting for up to 92.12%. The pores are concentrated in the tuffaceous section and well interconnected, forming a complex organic-inorganic pore-fracture network system and bedding fractures with even better connectivity. The pores of the tuffaceous section are greatly influenced by lithofacies and mineral composition. The porosities of tuffaceous mudstone, sedimentary tuff and tuff rank downward, with average porosities of 6.5%, 5.09%, and 3.86% respectively. The felsic content is inversely correlated with porosity; the clay content and TOC content are positively correlated with porosity; the pyrite content is also inversely correlated with porosity. The marine tuffaceous section is similar to shale to a certain extent as it has relatively dense lithology, its pores are mainly of micron-scale and nano-scale and mainly include micropores and mesopores. It boasts the hydrocarbon-generating capacity and reservoir performance, serving as both a source rock and a reservoir. As a novel reservoir, the tuffaceous section can form a tight reservoir both generating and depositing gas and featuring source-reservoir paragenesis, lithological reservoir-controlling, and large-area stratified distribution, manifesting a promising future for exploration

Lithofacies Characteristics and Pore Controlling Factors of New Type of Permian Unconventional Reservoir in Sichuan Basin

Alongside volcanic eruptions in the middle and late Permian, the sedimentary environment and process changed, and the lithofacies characteristics varied conspicuously in the marine deposits of the Sichuan Basin (China). The tuffaceous rocks, as a new type of unconventional reservoir, provide strong evidence for marine and volcanic influences on the lithology and reservoir potential of the rocks. With experimental studies relying on field outcrops, thin sections, scanning electron microscopy and whole-rock X-ray diffraction (XRD), the researchers analyzed the lithofacies characteristics, pore types and controlling factors on the various types of pores in the tuffaceous rocks. We identified three lithofacies types in this new type of Permian reservoir in the Sichuan Basin, namely tuff, sedimentary tuff, and tuffaceous mudstone. The mineral composition of the three lithofacies includes quartz, feldspar, carbonate minerals, pyrite, and clay, among which feldspar is mainly potassium feldspar. Tuff has high tuff content, and the lowest clay and TOC content; tuffaceous mudstones have the highest clay and TOC content, and the lowest tuff content. The pore types of the tuffaceous rocks are mainly nano-scale shrinkage pores, with a small number of intergranular pores including intragranular pores, intergranular pores, and organic pores. The shrinkage pores account for 81.9% of the total pores, and organic pores account for 11.2% of the total pores. In the tuffaceous rocks, the tuff content, quartz and feldspar content, and pyrite content are inversely correlated with porosity, while the clay content and TOC content are positively correlated with porosity. The porosity of tuff is the lowest, followed by sedimentary tuff, and the porosity of tuffaceous mudstone is the highest. Tuffaceous rocks form many micropores in the process of devitrification. Organic matter pyrolysis and organic acid dissolution also increase the reservoir space and porosity of the reservoir. This new type of reservoir has the ability of hydrocarbon accumulation along with the reservoir performance, and thus it has greater exploration prospects

MDS-Net: Multi-Scale Depth Stratification 3D Object Detection from Monocular Images

Monocular 3D object detection is very challenging in autonomous driving due to the lack of depth information. This paper proposes a one-stage monocular 3D object detection network (MDS Net), which uses the anchor-free method to detect 3D objects in a per-pixel prediction. Firstly, a novel depth-based stratification structure is developed to improve the network’s ability of depth prediction, which exploits the mathematical relationship between the size and the depth in the image of an object based on the pinhole model. Secondly, a new angle loss function is developed to further improve both the accuracy of the angle prediction and the convergence speed of training. An optimized Soft-NMS is finally applied in the post-processing stage to adjust the confidence score of the candidate boxes. Experiment results on the KITTI benchmark demonstrate that the proposed MDS-Net outperforms the existing monocular 3D detection methods in both tasks of 3D detection and BEV detection while fulfilling real-time requirements