master-degree-notes/.obsidian/workspace.json

321 lines
No EOL
10 KiB
JSON

{
"main": {
"id": "9c5b007ab74924bc",
"type": "split",
"children": [
{
"id": "8826bf446da15cf7",
"type": "tabs",
"children": [
{
"id": "1fb39a1dfc7b5200",
"type": "leaf",
"state": {
"type": "markdown",
"state": {
"file": "Biometric Systems/notes/7. Face recognition 3D.md",
"mode": "source",
"source": false
},
"icon": "lucide-file",
"title": "7. Face recognition 3D"
}
},
{
"id": "e85dead89a57b629",
"type": "leaf",
"state": {
"type": "pdf",
"state": {
"file": "Biometric Systems/slides/LEZIONE12_MULBIOMETRIC.pdf",
"page": 7,
"left": -8,
"top": 471,
"zoom": 1.91218487394958
},
"icon": "lucide-file-text",
"title": "LEZIONE12_MULBIOMETRIC"
}
},
{
"id": "5daa52ac6f774870",
"type": "leaf",
"state": {
"type": "markdown",
"state": {
"file": "Biometric Systems/notes/6. Face recognition 2D.md",
"mode": "source",
"source": false
},
"icon": "lucide-file",
"title": "6. Face recognition 2D"
}
},
{
"id": "d8fa8d03f085ad3e",
"type": "leaf",
"state": {
"type": "pdf",
"state": {
"file": "Biometric Systems/slides/LEZIONE8_Face antispoofing.pdf",
"page": 42,
"left": -9,
"top": 38,
"zoom": 1.0875000000000001
},
"icon": "lucide-file-text",
"title": "LEZIONE8_Face antispoofing"
}
},
{
"id": "a72e67571f49a527",
"type": "leaf",
"state": {
"type": "pdf",
"state": {
"file": "Foundation of data science/slides/Traditional discriminative approaches.pdf",
"page": 1,
"left": -18,
"top": 1978,
"zoom": 0.8485315504519935
},
"icon": "lucide-file-text",
"title": "Traditional discriminative approaches"
}
},
{
"id": "df3b868fc5f1ad74",
"type": "leaf",
"state": {
"type": "markdown",
"state": {
"file": "Foundation of data science/notes/9 Decision tree.md",
"mode": "source",
"source": false
},
"icon": "lucide-file",
"title": "9 Decision tree"
}
}
]
}
],
"direction": "vertical"
},
"left": {
"id": "e2078ffa3de56c07",
"type": "split",
"children": [
{
"id": "d86cb8d8115f9e4b",
"type": "tabs",
"children": [
{
"id": "2b2245f56092006e",
"type": "leaf",
"state": {
"type": "file-explorer",
"state": {
"sortOrder": "alphabetical"
},
"icon": "lucide-folder-closed",
"title": "Files"
}
},
{
"id": "954699747dc12b5e",
"type": "leaf",
"state": {
"type": "search",
"state": {
"query": "infraross",
"matchingCase": false,
"explainSearch": false,
"collapseAll": false,
"extraContext": false,
"sortOrder": "alphabetical"
},
"icon": "lucide-search",
"title": "Search"
}
},
{
"id": "71e92c2ed6f6f21c",
"type": "leaf",
"state": {
"type": "bookmarks",
"state": {},
"icon": "lucide-bookmark",
"title": "Segnalibri"
}
}
]
}
],
"direction": "horizontal",
"width": 307.5
},
"right": {
"id": "bc4b945ded1926e3",
"type": "split",
"children": [
{
"id": "00a3201508c9b6f7",
"type": "tabs",
"children": [
{
"id": "34cc5dc90419b254",
"type": "leaf",
"state": {
"type": "backlink",
"state": {
"file": "Autonomous Networking/notes/q&a.md",
"collapseAll": false,
"extraContext": false,
"sortOrder": "alphabetical",
"showSearch": false,
"searchQuery": "",
"backlinkCollapsed": false,
"unlinkedCollapsed": true
},
"icon": "links-coming-in",
"title": "Backlinks for q&a"
}
},
{
"id": "f4a0915b879a43cd",
"type": "leaf",
"state": {
"type": "outgoing-link",
"state": {
"file": "Autonomous Networking/notes/q&a.md",
"linksCollapsed": false,
"unlinkedCollapsed": true
},
"icon": "links-going-out",
"title": "Outgoing links from q&a"
}
},
{
"id": "c12ba700d0604b95",
"type": "leaf",
"state": {
"type": "tag",
"state": {
"sortOrder": "frequency",
"useHierarchy": true
},
"icon": "lucide-tags",
"title": "Tags"
}
},
{
"id": "77997770a5699d72",
"type": "leaf",
"state": {
"type": "outline",
"state": {
"file": "Autonomous Networking/notes/q&a.md"
},
"icon": "lucide-list",
"title": "Outline of q&a"
}
},
{
"id": "0d5325c0f9289cea",
"type": "leaf",
"state": {
"type": "git-view",
"state": {},
"icon": "git-pull-request",
"title": "Source Control"
}
},
{
"id": "cbc4870b4c7598e1",
"type": "leaf",
"state": {
"type": "chat-view",
"state": {
"file": "Chats/New Chat.md"
},
"icon": "lucide-file",
"title": "Plugin no longer active"
}
}
],
"currentTab": 4
}
],
"direction": "horizontal",
"width": 604.5,
"collapsed": true
},
"left-ribbon": {
"hiddenItems": {
"switcher:Open quick switcher": false,
"graph:Open graph view": false,
"canvas:Create new canvas": false,
"daily-notes:Open today's daily note": false,
"templates:Insert template": false,
"command-palette:Open command palette": false,
"obsidian-ocr:Search OCR": false,
"pdf-plus:PDF++: Toggle auto-copy": false,
"pdf-plus:PDF++: Toggle auto-focus": false,
"pdf-plus:PDF++: Toggle auto-paste": false,
"obsidian-git:Open Git source control": false,
"smart-second-brain:Open S2B Chat": false,
"companion:Toggle completion": false
}
},
"active": "1fb39a1dfc7b5200",
"lastOpenFiles": [
"Biometric Systems/notes/6. Face recognition 2D.md",
"Biometric Systems/notes/9. Ear recognition.md",
"Biometric Systems/notes/8 Face anti spoofing.md",
"Biometric Systems/notes/1. Introduction.md",
"Biometric Systems/notes/2. Performance indexes.md",
"Biometric Systems/notes/3. Recognition Reliability.md",
"Biometric Systems/slides/LEZIONE2bis_Indici_di_prestazione.pdf",
"Biometric Systems/slides/LEZIONE3_Affidabilita_del_riconoscimento.pdf",
"Biometric Systems/slides/LEZIONE2_Indici_di_prestazione.pdf",
"Biometric Systems/notes/12. Iris recognition.md",
"Biometric Systems/slides/LEZIONE10_Iris recognition.pdf",
"Biometric Systems/notes/11. Fingerprints.md",
"Biometric Systems/slides/LEZIONE12_MULBIOMETRIC.pdf",
"Foundation of data science/slides/Traditional discriminative approaches.pdf",
"Foundation of data science/notes/9 Gradient Boosting.md",
"Foundation of data science/notes/9 Decision tree.md",
"Foundation of data science/notes/9 K-Nearest Neighbors.md",
"Foundation of data science/notes/9 XGBoost.md",
"Foundation of data science/notes/9 Random Forest.md",
"Biometric Systems/slides/LEZIONE8_Face antispoofing.pdf",
"Biometric Systems/slides/LEZIONE11_Fingerprints.pdf",
"Biometric Systems/notes/13. Multi biometric.md",
"Biometric Systems/notes/7. Face recognition 3D.md",
"Biometric Systems/notes/4. Face detection.md",
"Foundation of data science/notes/3.1 Multi Class Logistic Regression.md",
"Foundation of data science/notes/3.2 LLM generated from notes.md",
"Foundation of data science/notes/2 Linear Regression.md",
"Foundation of data science/notes/3 Logistic Regression.md",
"Biometric Systems/frequently asked questions/Biomteric Systems.pdf",
"Biometric Systems/frequently asked questions/BS_oral_questions_16022021.md",
"Biometric Systems/frequently asked questions/BS_questions.txt.md",
"Foundation of data science/slides/Principal Component Analysis.pdf",
"Foundation of data science/notes/6 PCA.md",
"Foundation of data science/notes/8 Variational Autoencoders.md",
"Foundation of data science/notes/7 Autoencoders.md",
"Foundation of data science/notes/1 CV Basics.md",
"Biometric Systems/images/Pasted image 20241228171617.png",
"Biometric Systems/images/Pasted image 20241228174722.png",
"Biometric Systems/images/Pasted image 20241217025904.png",
"Biometric Systems/images/Pasted image 20241217030157.png",
"Biometric Systems/images/Pasted image 20241212094046.png",
"Biometric Systems/images/Pasted image 20241212094016.png",
"Biometric Systems/images/Pasted image 20241212093900.png",
"Biometric Systems/images/Pasted image 20241212084349.png",
"Biometric Systems/images/Pasted image 20241212094000.png",
"Biometric Systems/images/Pasted image 20241212093943.png",
"Senza nome.canvas"
]
}