## computer vision – Algorithm of deep image matting

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## PC Games – Deep Diving Simulator v 1.14 + DLC (2019) SpaceX | NulledTeam UnderGround

Deep diving simulator (v 1.19 + DLC) (2019) PC | RePack from SpaceX | Size: 2.62 GB

Release year: 2019
Genre: Simulation, Casual, Indie, 3D
Developer: Jujubee SA
Publisher: Jujubee SA
Version of the game: v1.14
Type of edition: repack
Interface language: English, MULTi Voice
The French language
Tablet: not required (without DRM)
A flawless stay

:
In the game "Underwater World Diving Simulator" you will get acquainted with the work of a modern diver. Study the unknown corners of the oceans slowly, watch the oxygen supply carefully and avoid decompression. Gather vestiges from the past, visit wrecks and discover new species of marine animals to receive the rewards of Professor Adams. During the dives, you will have the opportunity to discover many intriguing and sometimes terrible secrets, including the enigma of the legendary Atlantis.

Game Features:
Stunning graphics – experience the fantastic beauty of the world's oceans and people by diving into Arctic ice and tropical coral reefs.
An exciting game – every dive teaches you what a professional diver needs to know and be able to do. Learn how to monitor your oxygen intake and prevent the insidious decompression syndrome.
Underwater dangers – in the world you visit while diving, there are discreet stingrays, hungry sharks and many other deadly threats.
In Search of Secrets – by helping Professor Adams explore engulfed objects, you will learn many interesting things about our oceans.
Career progression – with each successful dive, you will receive better equipment that will allow you to visit previously closed areas.
Games Beyond ™ – participate in the salvation of the seas and oceans of the Earth by familiarizing yourself with the underwater world and its mysterious inhabitants.

RePack Features
Install and play!
Based on the GOG license (ID: 1952000880)
Version of the game: v1.14 (19/09/06)
EN / RU installer
Start the game from the desktop
Change the language in the game menu
100% audio quality
100% video quality

Required configuration:
√ Operating system: Windows7 / 8/10 (x64)
√ Processor: Intel Core i3-2100 / AMD FX-4350
√ RAM: 8 GB
√ Video card: GeForce GTX 670 / Radeon R9 380
√ Sound card: compatible with DirectX 11
√ Free disk space: 6 GB

## typescript – Access to the properties of the Typesafe deep object

I'm trying to type the method to update the deep object property:

Class Foo {
updateDeepObjectProperty(path: (K1, K2), value: T(K1)(K2)): void {
this.object = _set(path, value, this.object));
}
}


And use it like that

Class Bar {
onUpdateThing(value: number): void {
this.foo.updateDeepObjectProperty('deep.property', value;)
}
}


But the manuscript complains of the lack of type arguments.

It works well if I add object parameter to updateDeepObjectProperty but that's not what I'm looking for.

Is it possible to add a type argument for updateDeepObjectProperty but to continue to assign K1 …?

## deep learning – Using the neural network in data science

I know that neural networks are good and mainly used for face recognition, images and videos. A few days ago, I discovered how to use neural networks to detect cancer and other diseases (positive results). But are there simple projects or networks to use in the fields of data science, databases, audio, etc.? Something more important than training to find a word or something :). I am thinking of creating a small type of neural network in a data science company.

## sequences and series – Is there a philosophy or a deep intuition behind the similarity between $pi / 4$ and $e ^ {- gamma}$?

Here are some examples of similarity from Wikipedia, in which the expressions differ only in signs.
I have also met other analogies.

{ begin {aligned} gamma & = int _ {0} ^ {1} int _ {0} ^ {1} { frac {x-1} {(1-xy) ln xy} } , dx , dy \ & = sum {n = 1} ^ { infty} left ({ frac {1} {n}} – ln { frac {n + 1} {n} } right). end {aligned}}

{ begin {aligned} ln { frac {4} { pi}} & = int _ {0} ^ {1} int _ {0} ^ {1} { frac {x-1 } {(1 + xy) ln xy}} , dx , dy \ & = sum _ {n = 1} ^ { infty} left ((- 1) ^ {n-1} left ({ frac {1} {n}} – ln { frac {n + 1} {n}} right) right). end {aligned}}

{ begin {aligned} gamma & = sum _ {n = 1} ^ { infty} { frac {N_ {1} (n) + N_ {0} (n)} {2n (2n + 1)}} \ ln { frac {4} { pi}} & = sum _ {n = 1} ^ { infty} { frac {N_ {1} (n) -N_ {0} (n)} {2n (2n + 1)}}, end {aligned}}

I wonder if there is an algebraic system where $$4e ^ {- gamma}$$ would play a role similar to that $$pi$$ plays, say in complex numbers, or a geometric system where $$4e ^ {- gamma}$$ would play a special role, as $$pi$$ in Euclidean and Riemannian geometries.

## Detect positions and rotations of simple objects with Deep Learning [on hold]

how can i detect this object
in the

with deep learning

in a classic way we did and works, but I want to do with deep learning
no problem with the training data

## Neural Networks – The Deep Learning Model Outperforms Explicit Batch Sizes

I have created a thorough learning model for time series forecasting. The model works very well. I've tried different batch sizes 32, 50, 64, 100, 128 and 256.
I've got the best result for a batch size of 50. With a batch size of 32, the model still works, but the convergence of the error takes too much time.
I've tried several experiments with a batch size of 64. With this lot size, the model is not able to learn. The MAE is very high, the learning error decreases, but the validation error is very high. It seems that the model is too heavy for a lot size of 64.
I have therefore done other experiments with a batch size of 100, 128 and 256.
100 works of, but not as good as 50. 128 shows the same results as 64. 256 shows good results in training and validation error, but not in the MAE.
Do you have any ideas for which 64 and 128 do not work?
I know that models tend to over-adjust, when the lot size is too big, but this reason makes no sense to me in this case.

## javascript – JS deep melting of objects – removal of empty keys

I wrote a wizard to combine objects (deep fusion).

It works and is flexible to add options (like uniq and replace).

Replace should replace all the corresponding properties on the object (but distributed in the existing properties).

The code below works, but I think it could be optimized, especially because I could NOT find a way to remove empty keys without using JSON.parse(JSON.stringify – It is wrong to have to go through the entire matrix to do it.

Using Lodash is not an option.

## Examples

DATA = {foo: {i: {z: (1)}, x: (1)}}

• getDeepMerge(DATA, {add:{foo:{q:(1)}}}

// {foo: {i: {}, x: (1), q: (1)}}

• getDeepMerge(DATA, {add:{foo:{}}, replace:true}

// {foo: {}}

• getDeepMerge(DATA, {add:{foo:{i:{}}} }, replace:true, removeEmpty:true}

// {add: {foo: {i: {}}, x (1)}}

## Code

const removeKey = (key, {(key): _, ...rest}) => rest;

const DE_DUPE = (e, i, arr) => arr.indexOf(e) === i

const removeEmptyObj = (o) => {
let ignores = (null, undefined, ""),
isNonEmpty = d => !ignores.includes(d) && (typeof(d) !== "object" || Object.keys(d).length)
return JSON.parse(JSON.stringify(o), function(k, v) {
if (isNonEmpty(v))
return v;
});
}
const getDeepMerge = (ogObj, opts={})=> {
const { add, uniq=true, replace=false, removeEmpty=false } = opts

const isObject = obj => obj && typeof obj === 'object';
return (ogObj, add).reduce((prev, obj) => {
Object.keys(obj).forEach(key => {

const oVal = obj(key);

if (Array.isArray(pVal) && Array.isArray(oVal)) {
_add(key) = pVal.concat(...oVal).filter(uniq ? DE_DUPE : null)
if(replace){

}
else if (isObject(pVal) && isObject(oVal)) {
if(replace){
}
}
else {
}
});
}, {});
}


Demonstration of live work: https://jsbin.com/yuduvukiqe/1/edit?js,console

## [ Other – Education ] Open question: Why are mortgage interest rates falling in a deep recession?

[Other – Education] Open question: Why are mortgage interest rates falling in times of deep recession?

## dnd 5th – How deep is the Underdark? What is its maximum and median depth?

### At least 26 miles deep, with unexplored rumored caves 40 miles deep, although most of the known Underdark are within 10 miles of the surface.

According to the sourcebook D & D 3rd Underdark, p.120, the lowest level of the Underdark begins at a depth of ten miles and continues from there:

No place on Toril is as strange and dangerous as the Lowerdark. This level of Underdark extends from 10 miles below the surface at unfathomable depths and has a degree of strangeness that would drive some people off the surface.

At this depth, it is described that tunnels and passages become rarer. Since it's the bottom of the Underdark, the typical depth Underdark locations is between 1 and 10 miles below the surface. For example, the town of Menzoberranzan is only 3 km from the surface and is considered part of the Upperdark.

### The deepest places

The portals to the Shadow Plane (which would be called in 5th Shadowfell) would exist at depths of 15 miles or less. A sea sinks 20 miles below the surface (p.123):

The Glimmersea is 20 miles below the ground of the sea of ​​fallen stars.

The city of Genasi from Earth's End (p.147) is even deeper, although it can not be reached without teleportation and does not have direct tunnels:

situated almost 22 miles Under the Nath at Halruaa, Earth's End was designed without any discomfort for its extraplanar visitors.

Oryndoll, City of Loretakers, is just over 26 km deep (p.168).

There is also an abyss under Anauroch, named Lorosfyr, deadly darkness, it is said to be at least 40 miles deep in places (p.160), although it is unexplored.