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File:Simplified neural network training example.svg

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188: 43: 236: 268: 157:: The network is trained by multiple images that are known to depict starfish and sea urchins, which are correlated with "nodes" that represent visual aspects, in this case texture and outline. The starfish match with a ringed texture and a star outline, whereas most sea urchins match with a striped texture and oval shape. However, the instance of a ring shaped sea urchin creates a weakly weighted association between them. 298: 304: 99: 273:
Subsequent run of the network on an input image (left): The network correctly detects the starfish. However, the weakly weighted association between ringed texture and sea urchin also confers a weak signal to the latter from one of two intermediate nodes. In addition, a shell that was not included in
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261:. The starfish match with a ringed texture and a star outline, whereas most sea urchins match with a striped texture and oval shape. However, the instance of a ring textured sea urchin creates a weakly weighted association between them. 716: 691: 69: 73: 65: 61: 57: 53: 47: 110: 82: 673: 274:
the training gives a weak signal for the oval shape, also resulting in a weak signal for the sea urchin output. These weak signals may result in a
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153:Simplified example of training a neural network in 335:Creative Commons Zero, Public Domain Dedication 143:Simplified neural network training example.svg 98: 8: 46:Size of this PNG preview of this SVG file: 734: 576: 363:Simplified neural network training example 359: 314:CC0 1.0 Universal Public Domain Dedication 684:The following other wikis use this file: 674:Training, validation, and test data sets 297: 186: 744: 736: 659:Hallucination (artificial intelligence) 636: 550: 534: 516: 500: 482: 466: 446: 430: 410: 394: 377: 374: 355: 348: 309:This file is made available under the 7: 565: 727: 368: 362: 147: 130: 80: 664:Neural network (machine learning) 367: 241:Simplified example of training a 353: 302: 296: 266: 234: 97: 31: 21: 702:Neuronska mreža širenja unapred 350: 303: 148: 14: 717:Галюцинація (штучний інтелект) 349: 26: 1: 553:original creation by uploader 36: 449:Creative Commons CC0 License 375:Items portrayed in this file 766: 708:Usage on uk.wikipedia.org 698:Usage on sr.wikipedia.org 688:Usage on ml.wikipedia.org 654:Feedforward neural network 649:Feature (computer vision) 566: 295: 285: 176: 16: 352: 207:- Conflicts of interest: 104:This is a file from the 623: 182: 172: 165: 162: 140: 108:. Information from its 278:result for sea urchin. 210: 111:description page there 602:18:27, 2 October 2023 190: 70:1,791 × 2,048 pixels 52:Other resolutions: 692:കൃത്രിമ നാഡീവ്യൂഹം 211: 66:895 × 1,024 pixels 753: 752: 680:Global file usage 627: 433:copyright license 361: 347: 346: 222: 221: 126: 125: 106:Wikimedia Commons 32:Global file usage 757: 735: 712:Глибоке навчання 669:Object detection 619:Mikael Häggström 614: 397:copyright status 342: 339: 336: 333: 330: 311:Creative Commons 306: 305: 300: 299: 293: 270: 247:object detection 238: 213:Mikael Häggström 192:Mikael Häggström 178: 168: 155:object detection 152: 144: 138: 122: 101: 100: 94: 88: 77: 74:773 × 884 pixels 62:672 × 768 pixels 58:420 × 480 pixels 54:210 × 240 pixels 48:524 × 599 pixels 765: 764: 760: 759: 758: 756: 755: 754: 723: 678: 639:Computer vision 635: 628: 620: 612: 568: 567: 564: 563: 562: 561: 560: 559: 558: 557: 555: 543: 542: 541: 539: 528: 527: 526: 525: 524: 523: 522: 521: 519: 509: 508: 507: 505: 494: 493: 492: 491: 490: 489: 488: 487: 485: 475: 474: 473: 471: 460: 459: 458: 457: 456: 455: 454: 453: 451: 439: 438: 437: 435: 424: 423: 422: 421: 420: 419: 418: 417: 415: 403: 402: 401: 399: 388: 387: 386: 385: 384: 382: 366: 365: 364: 340: 337: 334: 331: 328: 291: 283: 282: 281: 280: 279: 271: 263: 262: 239: 228: 223: 158: 142: 135: 128: 127: 116: 115: 114:is shown below. 90: 86: 79: 78: 51: 12: 11: 5: 763: 761: 751: 750: 747: 743: 742: 739: 726: 722: 721: 720: 719: 714: 706: 705: 704: 696: 695: 694: 682: 681: 677: 676: 671: 666: 661: 656: 651: 646: 641: 633: 632: 631: 626: 625: 622: 618: 615: 609: 604: 599: 595: 594: 591: 588: 585: 582: 579: 572: 571: 556: 551: 549: 548: 547: 546: 545: 544: 540: 537:source of file 535: 533: 532: 531: 530: 529: 520: 517: 515: 514: 513: 512: 511: 510: 506: 501: 499: 498: 497: 496: 495: 486: 484:2 October 2023 483: 481: 480: 479: 478: 477: 476: 472: 467: 465: 464: 463: 462: 461: 452: 447: 445: 444: 443: 442: 441: 440: 436: 431: 429: 428: 427: 426: 425: 416: 411: 409: 408: 407: 406: 405: 404: 400: 395: 393: 392: 391: 390: 389: 383: 378: 376: 373: 372: 371: 370: 369: 358: 357: 354: 351: 345: 344: 318: 317: 307: 290: 287: 276:false positive 272: 265: 264: 243:neural network 240: 233: 232: 231: 230: 229: 227: 224: 220: 219: 204:Reusing images 184: 180: 179: 174: 170: 169: 167:2 October 2023 164: 160: 159: 145: 136: 134: 131: 129: 124: 123: 102: 92: 91: 45: 41: 40: 39: 34: 29: 24: 19: 13: 10: 9: 6: 4: 3: 2: 762: 748: 745: 740: 737: 733: 730: 724: 718: 715: 713: 710: 709: 707: 703: 700: 699: 697: 693: 690: 689: 687: 686: 685: 679: 675: 672: 670: 667: 665: 662: 660: 657: 655: 652: 650: 647: 645: 644:Deep learning 642: 640: 637: 629: 621: 616: 610: 608: 605: 603: 600: 597: 596: 592: 589: 586: 583: 580: 578: 577: 575: 569: 554: 538: 518:image/svg+xml 504: 470: 450: 434: 414: 398: 381: 343: 324: 323:public domain 320: 319: 315: 312: 308: 294: 288: 286: 277: 269: 260: 256: 252: 248: 244: 237: 225: 218: 214: 208: 206: 205: 201: 200: 197: 193: 189: 185: 181: 175: 171: 161: 156: 151: 146: 139: 132: 120: 113: 112: 107: 103: 96: 95: 89: 84: 83:Original file 75: 71: 67: 63: 59: 55: 49: 44: 38: 35: 33: 30: 28: 25: 23: 20: 18: 15: 731: 728: 683: 573: 570:File history 327: 284: 149: 119:You can help 109: 81: 22:File history 741:218.29454mm 255:sea urchins 209:  None 199:Author info 141:Description 749:249.5381mm 630:File usage 611:773 × 884 587:Dimensions 503:media type 27:File usage 584:Thumbnail 581:Date/Time 469:inception 289:Licensing 150:English: 725:Metadata 356:Captions 259:features 251:starfish 177:Own work 37:Metadata 613:(96 KB) 598:current 593:Comment 380:depicts 360:English 226:Context 133:Summary 85:‎ 746:Height 301:  183:Author 173:Source 738:Width 341:false 338:false 590:User 253:and 217:M.D. 196:M.D. 163:Date 17:File 332:CC0 245:in 316:. 215:, 202:- 194:, 72:| 68:| 64:| 60:| 56:| 50:. 121:. 76:.

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File:Simplified neural network training example.svg
524 × 599 pixels
210 × 240 pixels
420 × 480 pixels
672 × 768 pixels
895 × 1,024 pixels
1,791 × 2,048 pixels
773 × 884 pixels
Original file
Wikimedia Commons
description page there
You can help
object detection

Mikael Häggström
M.D.
Author info
Reusing images
Mikael Häggström
M.D.

neural network
object detection
starfish
sea urchins

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