Remote sensing image object detection has been studied by many researchers in recent years using deep neural networks. However, optical remote images contain scenes with small and dense objects, resulting a high rate of misrecognition. Firstly, this work we selected layer aggregation network updated deformable convolution layers as the backbone to extract features. The classification objects wa...

Accurate detection of multi-class instance objects in remote sensing images (RSIs) is a fundamental but challenging task the field aviation and satellite image processing, which plays crucial role wide range practical applications. Compared with natural image-based object task, RSIs-based still faces two main challenges: 1) The often present large variations size, they are densely arranged give...

For representing high level knowledge, such as the mathematical knowledge used in interactive theorem provers and veriication systems, it is desirable to extend Prolog's concept of data object. A basic reason is that Prolog data objects | Herbrand objects | are terms of a minimal object language, which does not include its own object variables, or quantiication over those variables. Qu-Prolog (...

We present new distributed randomized naming protocols improving previous results in renaming and unique processor identity protocols. They are wait-free (which implies maximal fault-tolerance) and allow stronger adversaries. They also have low complexity. We give the rst wait-free protocol achieving optimal key space range. (This is impossible for deterministic wait-free methods, so we use ran...

forest classification on the basis of satellite images is a promising technique both for primary map production and for map updating and forest monitoring. for accurate for-est classification into three classes, using mapping by canopy cover density “high spatial resolution satellite images have to be used in order to obtain the required spatial detail” [schneider, 1999]. at the same time, the ...

The experiments reported here were designed to explore the bizarreness effect in implicit and explicit memory by using simple line drawings of common objects (normal vs. bizarre). Each drawing was presented alone under mixed-list encoding conditions. Results showed that performance on explicit conceptual memory tests (cued recall in Experiments 1 and 2) was higher when material was studied in a...

Potential functions are used to represent the topological structure of free space in solving path planning problems because of the simplicity in the free space representation and the guidance provided by the negative gradient of the potential field in the form of repulsive force. In this paper, Newtonian potential function is used to represent polygonal objects and obstacles. The closedform exp...

Vitalism was abandoned already for a long time ago, yet the impression that animate beings differ in some fundamental way from inanimate objects continues to thrive. Here, we argue that scale free patterns, found throughout nature, present convincing evidence that this demarcation is only imaginary. Therefore, all systems ought to be regarded alike, i.e., all are consuming free energy in least ...

Segmenting 3D object surfaces is required for various high level computer vision and computer graphics applications. In computer vision, recognizing and estimating poses of 3D objects heavily depend on segmentation results. Similarly, physically meaningful segments of a 3D object may be useful in various computer graphics applications. Therefore, there are many segmentation algorithms proposed ...