LEVIR-CD is a new large-scale remote sensing binary change detection dataset, which would help develop novel deep learning-based algorithms for remote sensing image change detection.
Overview of LEVIR-CD
LEVIR-CD is a new large-scale remote sensing building Change Detection dataset. The introduced dataset would be a new benchmark for evaluating change detection (CD) algorithms, especially those based on deep learning.
LEVIR-CD consists of 637 very high-resolution (VHR, 0.5m/pixel) Google Earth (GE) image patch pairs with a size of 1024 × 1024 pixels. These bitemporal images with time span of 5 to 14 years have significant land-use changes, especially the construction growth. LEVIR-CD covers various types of buildings, such as villa residences, tall apartments, small garages and large warehouses. Here, we focus 提供外汇交易商Binary简介 on building-related changes, including the building growth (the change from soil/grass/hardened ground or building under construction to new build-up regions) and the building decline. These bitemporal images are annotated by remote sensing image interpretation experts using binary labels (1 for change and 0 for unchanged). Each sample in our dataset is annotated by one annotator and then double-checked by another to produce high-quality annotations. The fully annotated LEVIR-CD contains a total of 31,333 individual change building instances.
Geospatial Distribution of LEVIR-CD
The bitemporal images in LEVIR-CD are from 20 different regions that sit in several cities in Texas of the US, including Austin, Lakeway, Bee Cave, Buda, Kyle, Manor, Pflugervilletx, Dripping Springs, etc. The Figure below illustrates the geospatial distribution of our new dataset and an enlarged image patch. The captured time of our image data varies from 2002 to 2018. Images in different regions 提供外汇交易商Binary简介 may be taken at different times. We want to introduce variations due to seasonal changes and illumination changes into our new dataset, which could help develop effective methods that can mitigate the impact of irrelevant changes on real changes.
Examples of annotated samples
Samples size of 1024 × 1024
Cropped samples size of 256 × 256
We are from LEVIR, which is the abbreviation of ours’ laboratory: LEarning, VIsion and Remote sensing laboratory. Visit the lab homepage for more details.
If you have any the problem or feedback in using LEVIR-CD, please contact
A character string literal, hexadecimal literal, or bit-value literal may have an optional character set introducer and COLLATE clause, to designate it as a string that uses a particular character set and collation:
The _ charset_name expression is formally called an introducer . It tells the parser, “ the string that follows uses character set charset_name . ” An introducer does not change the string to the introducer character set like CONVERT() would do. It does not change the string 提供外汇交易商Binary简介 value, although padding may occur. The introducer is just a signal.
For character string literals, space between the introducer and the string is permitted but optional.
For character set literals, an introducer indicates the character set for the following string, but does not change how 提供外汇交易商Binary简介 the parser performs escape processing within the string. Escapes are always 提供外汇交易商Binary简介 interpreted by the parser according to the character set given by character_set_connection . For additional discussion and examples, see Section 10.3.6, “提供外汇交易商Binary简介 Character String Literal Character Set and Collation”.
Character set introducers and the COLLATE clause are implemented according to standard SQL specifications.
Character string 提供外汇交易商Binary简介 literals can be designated as binary strings by using the _binary introducer. Hexadecimal literals and bit-value literals are binary strings by default, so _binary is permitted, but unnecessary.
MySQL determines the character set and collation of a character string literal, hexadecimal literal, or bit-value literal in the following manner:
If both _charset_name and COLLATE collation_name 提供外汇交易商Binary简介 are specified, character set charset_name and collation collation_name are used. collation_name must be a permitted collation for charset_name .
If _charset_name is specified but COLLATE is not specified, character set charset_name and its default collation are used. To see the default collation for each character set, use the SHOW CHARACTER SET statement or query the INFORMATION_SCHEMA CHARACTER_SETS table.
If _charset_name is not specified but COLLATE collation_name is specified:
For a character string literal, the connection default character set given by the character_set_connection system variable and collation collation_name are used. collation_name must be a permitted collation for the connection default character set.
For a hexadecimal literal or bit-value literal, the only permitted collation is binary because these types of literals are binary strings by default.
Otherwise (neither _charset_name nor COLLATE collation_name is specified):
For a character string literal, the connection default character set and collation given by the character_set_connection and collation_connection system variables are used.
For a hexadecimal literal or bit-value literal, the character set and collation are binary .
Nonbinary strings with latin1 character set and latin1_german1_ci collation:
Nonbinary strings with 提供外汇交易商Binary简介 utf8 character set and its default collation (that is, utf8_general_ci ):
Binary 提供外汇交易商Binary简介 strings with binary character set and its default collation (that is, binary ):
The hexadecimal literal and bit-value literal need no introducer because they are binary strings by default.
A nonbinary string with the connection default character set and utf8_general_ci collation (fails if the connection character set is not utf8 ):
This construction ( COLLATE only) does not work for hexadecimal literals or bit literals because their character set is binary no matter the connection character set, and binary is not compatible with the utf8_general_ci collation. The only permitted COLLATE clause in the absence of an introducer is COLLATE binary .
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"TEA" 的全称为"Tiny Encryption Algorithm" 是1994年由英国剑桥大学的David j.wheeler发明的.
在安全学领域，TEA（Tiny Encryption Algorithm）是一种分组加密算法，它的实现非常简单，通常只需要很精短的几行代码。TEA 算法最初是由剑桥计算机实验室的 David Wheeler 和 Roger Needham 在 1994 年设计的。
TEA算法使用64位的明文分组和128位的密钥，它使用Feistel分组加密框架，需要进行 64 轮迭代，尽管作者认为 32 轮已经足够了。该算法使用了一个神秘常数δ作为倍数，它来源于黄金比率，以保证每一轮加密都不相同。但δ的精确值似乎并不重要，这里 TEA 把它定义为 δ=「(√5 - 1)231」（也就是程序中的 0×9E3779B9）。
之后 TEA 算法被发现存在缺陷，作为回应，设计者提出了一个 TEA 的升级版本——XTEA（有时也被称为“tean”）。XTEA 跟 TEA 使用了相同的简单运算，但它采用了截然不同的顺序，为了阻止密钥表攻击，四个子密钥（在加密过程中，原 128 位的密钥被拆分为 4 个 32 位的子密钥）采用了一种不太正规的方式进行混合，但速度更慢了
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