Abstract: The invention discloses a method for glass detection in a real scene, which belongs to the field of object detection. The present invention designs a combination method based on LCFI blocks to effectively integrate context features of different scales. Finally, multiple LCFI combination blocks are embedded into the glass detection network GDNet to obtain large-scale context features of different levels, thereby realize reliable and accurate glass detection in various scenarios. The glass detection network GDNet in the present invention can effectively predict the true area of glass in different scenes through this method of fusing context features of different scales, successfully detect glass with different sizes, and effectively handle with glass in different scenes. GDNet has strong adaptability to the various glass area sizes of the images in the glass detection dataset, and has the highest accuracy in the field of the same type of object detection.

Abstract: The invention discloses a method for glass detection in a real scene, which belongs to the field of object detection. The present invention designs a combination method based on LCFI blocks to effectively integrate context features of different scales. Finally, multiple LCFI combination blocks are embedded into the glass detection network GDNet to obtain large-scale context features of different levels, thereby realize reliable and accurate glass detection in various scenarios. The glass detection network GDNet in the present invention can effectively predict the true area of glass in different scenes through this method of fusing context features of different scales, successfully detect glass with different sizes, and effectively handle with glass in different scenes. GDNet has strong adaptability to the various glass area sizes of the images in the glass detection dataset, and has the highest accuracy in the field of the same type of object detection.

Abstract: The invention belongs to the field of computer vision technology, and provides a fully automatic natural image matting method. For image matting of a single image, it is mainly composed of the extraction of high-level semantic features and low-level structural features, the filtering of pyramid features, the extraction of spatial structure information, and the late optimization of the discriminator network. The invention can generate accurate alpha matte without any auxiliary information, saving the time for scientific researchers to mark auxiliary information and the interaction time when users use it.

Abstract: The invention belongs to the field of computer vision technology, and provides a fully automatic natural image matting method. For image matting of a single image, it is mainly composed of the extraction of high-level semantic features and low-level structural features, the filtering of pyramid features, the extraction of spatial structure information, and the late optimization of the discriminator network. The invention can generate accurate alpha matte without any auxiliary information, saving the time for scientific researchers to mark auxiliary information and the interaction time when users use it.

Abstract: The invention relates to the field of strand displacement, and provides a color image encryption method based on a DNA strand displacement analog circuit. Firstly, a reaction module with a light-emitting group and a quenching group is designed through Visual DSD software, and by utilizing the equivalence of a DNA strand displacement reaction module and an ideal reaction module, an analog circuit formed by the DNA strand displacement reaction module can perform analog on the dynamics characteristics of an ideal reaction network formed by the ideal reaction module, wherein the Rössler chaotic system can be described by the idealized reaction network. Secondly, data generated by the DNA strand displacement analog circuit is converted into a chaotic sequence matched with a plaintext image in size after being extended, and finally, the color image encryption effect is achieved through scrambling and diffusion operations.

Abstract: The present invention discloses a ringtone uploading service method and system used in color ring back tone (CRBT) service. The present invention is that when a ringtone system successfully uploads a ringtone to at least one but not all ringtone servers, it records ringtone uploading information, sends a message about the successful uploading of the ringtone to an uploading terminal, and re-uploads the ringtone to the ringtone servers to which the ringtone has not been successfully uploaded. The ringtone uploading solution proposed in the present invention will greatly improve the success rate of ringtone uploading.

Abstract: The present invention discloses a ringtone uploading service method and system used in color ring back tone (CRBT) service. The present invention is that when a ringtone system successfully uploads a ringtone to at least one but not all ringtone servers, it records ringtone uploading information, sends a message about the successful uploading of the ringtone to an uploading terminal, and re-uploads the ringtone to the ringtone servers to which the ringtone has not been successfully uploaded. The ringtone uploading solution proposed in the present invention will greatly improve the success rate of ringtone uploading.

Abstract: Multiple features of email traffic are analyzed and extracted. Feature vectors comprising the multiple features are created and cluster analysis is utilized to track spam generation even from dynamically changing or aliased IP addresses.