[Retracted] A Deep Learning-Based Piano Music Notation Recognition Method

<div>The score (a) and the result of the corrosion operation of <svg height="8.8423pt" id="M30" style="vertical-align:-0.2064009pt" version="1.1" viewbox="-0.0498162 -8.6359 33.0216 8.8423" width="33.0216pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M686 28C612 35 607 44 591 112C563 234 541 360 519 489L489 666L457 658L147 121C100 40 89 36 24 28L17 0H240L250 28C168 34 159 41 190 101L262 237H482C495 180 503 137 510 91C517 47 514 35 441 28L433 0H677L686 28ZM475 280H285L429 541H431L475 280Z"></path></g><g transform="matrix(.013,0,0,-0.013,9.135,0)"><path d="M377 665C166 665 44 494 44 317C44 126 183 -15 363 -15C547 -15 695 118 695 333C695 533 546 665 377 665ZM355 630C491 630 593 515 593 304C593 112 496 22 385 22C245 22 146 157 146 345S244 630 355 630ZM502 225V442H471C464 375 459 369 411 369H326C278 368 273 374 266 442H235V225H266C273 292 278 299 326 299H411C459 299 464 292 471 225H502Z"></path></g><g transform="matrix(.013,0,0,-0.013,18.742,0)"><path d="M578 512C578 619 494 650 387 650H140L134 622C219 615 223 609 210 542L127 119C112 40 104 34 23 28L17 0H235C317 0 387 7 444 33C515 65 564 122 564 195C564 289 495 335 412 352V354C505 373 578 422 578 512ZM486 510C486 422 423 367 314 367H257L294 565C299 591 305 602 315 608C324 614 339 617 362 617C421 617 486 595 486 510ZM466 200C466 100 393 35 296 35C222 35 198 51 212 127L250 333H303C388 333 466 303 466 200Z"></path></g><g transform="matrix(.013,0,0,-0.013,26.555,0)"><path d="M412 140C382 77 369 73 315 73H129L270 222C362 320 402 379 402 466C402 571 322 635 234 635C177 635 130 609 99 576L42 495L64 475C90 514 133 568 201 568C274 568 318 519 318 435C318 349 255 267 193 193C144 135 87 78 32 23V0H405C417 45 427 89 440 131L412 140Z"></path></g></svg> (b).</div>

Computational Intelligence and Neuroscience

fig5

Figure 5

Figure 5: [Retracted] A Deep Learning-Based Piano Music Notation Recognition Method 