38 results about "Scale sliding" patented technology

A system for automated geospatial image analysis comprising a deep learning model module and a convolutional neural network serving as an automated image analysis software module. The deep learning module receives a plurality of orthorectified geospatial images, pre-labeled to demarcate objects of interest, and optimized for the purpose of training the neural network of the image analysis software module. The module presents marked geospatial images and a second set of unmarked, optimized, training geospatial images to the convolutional neural network. This process may be repeated so that an image analysis software module can detect multiple object types or categories. The image analysis software module receives a plurality of orthorectified geospatial images from one or more geospatial image caches. Using multi-scale sliding window submodule, image analysis modules scan geospatial images, detect objects present and locate them on the geographical latitude-longitude system. The system reports the results in the requestor's preferred format.

The present invention provides a road traffic sign detection and identification method. The method comprises the steps of: extracting a region of interest; performing multi-scale sliding traversal; merging image features; and identifying a traffic sign. The method specifically comprises: performing extraction of a region of interest of the traffic sign on an input to-be-detected image; convertingthe to-be-detected image into a gray-scale image; constructing a binary mask image of the region of interest of the traffic sign; performing multi-scale sliding traversal on the gray-scale image and the binary mask image to obtain position coordinates of a detected target; merging the extracted local texture features, local image region features and global features of the to-be-detected image; andclassifying and identifying the merged image features by using a classifier. The present invention relates to an electronic device and a readable storage medium for performing the road traffic sign detection and identification method; and the present invention also relates to a road traffic sign detection and identification system. The technical scheme of the present invention has a high detection rate, a high identification rate, a fast calculation speed, a low false detection rate and good robustness.

The invention discloses an adjustable water-injection ablation electrode needle, and belongs to the field of operating instruments for electrosurgery and the field of operating instruments for minimally invasive ablation. The electrode needle comprises a needle rod, a handle, an adjusting knob, an adjusting sleeve, a scale sliding block, a needle rod fixed seat, a water pipe fixed seat, a water pipe and radio frequency cables, wherein the tip end of the needle rod is composed of a triangular blade which is easy for puncture, and a thin hole is formed in the needle rod; an annular groove is formed in the handle, and a length-adjusting graduation ruler is arranged on the edge of the annular groove; an outer screw thread is formed in the adjusting knob, and the adjusting knob is composed of a plurality of edges provided with rounded corners; the adjusting sleeve and the scale sliding block are bonded by virtue of glue; an inner screw thread, which is matched with the adjusting knob, is formed in the scale sliding block; a scale indicating line is printed on the scale sliding block; the needle rod fixed seat and the needle rod are connected by virtue of glue; the water pipe fixed seat and the water pipe are connected by virtue of glue; and the radio frequency cables are welded on the needle rod. The adjustable water-injection type ablation needle disclosed by the invention is convenient to operate and clear in scale, and the ablation needle is convenient for doctors to observe in an operation.

The invention discloses an automatic aircraft weight center of gravity measuring apparatus and a control method thereof. The apparatus herein includes a fixed front scale and a fixed rear scale. The center lines of the fixed front scale and the fixed rear scale are provided with a sliding middle scale thereon, and the fixed front scale, the fixed rear scale and the sliding middle scale form a triangle. The fixed front scale and the fixed rear scale both include a digital weighing table. Each digital weighing table is connected to a lifting structure therebelow. The digital weighing table is also provided with a laser displacement sensor therebelow. The sliding middle scale includes a digital weighing table. The digital weighing table is connected to a lifting structure therebelow. The lifting structure is disposed on a scale sliding module. The apparatus herein can automatically measure the weight center of gravity of various kinds of aircrafts, and effectively addresses great measurement errors and high measurement cost due to differences of weighing devices upon measuring the weight center of gravity of various kinds of aircrafts.

The invention provides a stratum mobility simulating device. The stratum mobility simulating device comprises a constant speed and constant pressure pump, an intermediate container, a high temperature and high pressure sample allocation device and a model mechanism, wherein one end of the intermediate container is connected with the constant speed and constant pressure pump, one end of the high temperature and high pressure sample allocation device is provided with an air infusion port, the other end of the high temperature and high pressure sample allocation device is connected with the constant speed and constant pressure pump, the model mechanism comprises a flowing section, a capillary tube section and a phase volume fraction tester, the flowing section is provided with a mold section, the mold section comprises a fixed clamping groove and a movable clamping groove, the movable clamping groove can be movably arranged in a scale sliding groove, flat panel grooves are formed in the scale sliding groove, a convection current channel is formed between the fixed clamping groove and the movable clamping groove, the two ends of the convection current channel are the inlet end and the outlet end, the inlet end is connected with the other end of the intermediate container and the end, where the air infusion port is formed, of the high temperature and high pressure sample allocation device, and the outlet end is sequentially connected with the capillary tube section and the phase volume fraction tester. The stratum mobility simulating device is capable of simulating fissures of different opening degrees and stratums with different roughness and the flowing of single-phase fluid or multi-phase fluid in the stratums at different flowing speed, through the arrangement of a corestone, the conditions of the stratums can be simulated in a more realistic mode, the data are accurate, and the application range is wide.

The invention discloses a large-scale sliding block structure for preventing a product from burring. The large-scale sliding block structure is used for forming a larger entire surface. The large-scale sliding block structure comprises a cavity insert, a core cavity and a large-scaling sliding block, wherein the core insert is combined with the cavity insert to form the product; the large-scale sliding block is arranged between the core insert and the cavity insert to form the larger entire surface of the product, and an inserting breaking parting plane is arranged between the large-scale sliding block and the core insert. Compared with the prior art, the large-scale sliding block structure for preventing the product from burring, disclosed by the invention, has the advantages that because the inserting breaking parting plane is adopted between the large-scale sliding block and the core insert, even if the large-scale sliding block bears a larger forming pressure when injection molding is performed, the large-scale sliding block retreats when being impacted, a gap generated by the inserting breaking parting plane between the large-scale sliding block and the core insert is relatively small, plastic can not enter the gap, so that the product can not form burrs.

The invention discloses a human body detection method based on sample transfer learning. The human body detection method based on sample transfer learning comprises the following steps: multi-dimensional human body features of positive samples and negative samples in a training set are extracted; a support vector machine is used for training to obtain an initial human body detector; the human body detector is divided into a plurality of small grids, wherein each small grid represents a small component, and the weight of the corresponding grid is used for representing the small component; the weight of the grids is updated; human body detection is conducted on an image to be detected in a scanning mode through a multi-scale sliding frame, and therefore a human body detection result is obtained. According to the human body detection method based on sample transfer learning, the detector can be structurally adjusted in a self-adaptive mode so as to be matched with the structure of the samples in a detection frame and reckon in matching loss into a scoring function, and therefore the human body detection method can be used for conducting structural transferring on each sample in a self-adaptive mode and processing shape change in a human body and other conditions.

The invention discloses a method for dividing a level set image based on characteristics of a neighborhood probability density function, which mainly solves the problem existing in the prior method that the variability of texture elements of a natural image in texture scale and texture direction cannot be effectively processed. The method comprises the following steps of: initializing a level setfunction; setting an initial value and a maximum value for the iteration number of the level set function; working out a characteristic set of the neighborhood probability density function; working out characteristics of a subset probability density function; working out a similarity vector; according to an evolution equation of the level set, updating the level set function; judging whether to enter a cycle, if so, working out the characteristics of the subset probability density function, the similarity vector and the level set function again; otherwise stopping the cycle, and using a zero level set of the level set function as a segmentation border of an input image. Because the texture elements of the natural image are fit by a multi-scale sliding window, the variability of the textureelements in texture scale and texture direction can be better processed, so that the method can be applied to the segmentation of the natural texture image.