Research on Pedestrian Detection Algorithm Based on MobileNet-YoLo

<table class="table-group" id="tab5"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Loss function</td><td class="align_center">mAP (%)</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left"><span style="width: 23.446ptpx;"><svg height="11.9316pt" id="M72" style="vertical-align:-3.2957pt" version="1.1" viewbox="-0.0498162 -8.6359 23.446 11.9316" width="23.446pt" 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="M541 160L512 170C485 116 462 88 439 67C411 41 376 35 318 35C272 35 238 37 224 48C207 61 205 85 212 121L290 533C305 611 308 615 391 622L397 650H139L133 622C217 615 221 612 206 533L126 118C111 41 103 34 23 26L17 0H474C489 31 528 124 541 160Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.294,3.132)"><path d="M308 0V33C225 38 217 44 217 128V521C217 605 225 612 308 617V650H39V617C122 612 130 605 130 521V128C130 44 122 38 39 33V0H308Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,11.242,3.132)"><path d="M262 451C169 451 38 375 38 210C38 98 121 -12 261 -12C360 -12 481 64 481 227C481 351 386 451 262 451ZM249 414C337 414 385 320 385 204C385 70 333 25 272 25C189 25 134 117 134 241C134 355 189 414 249 414Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,15.964,3.132)"><path d="M727 650H480V617C552 612 575 600 580 563C583 531 587 491 587 398V326C587 153 534 44 398 44C281 44 210 124 210 296V519C210 607 218 612 298 617V650H33V617C114 609 123 607 123 519V274C123 153 151 81 211 34C258 -1 314 -14 374 -14C441 -14 509 7 556 56C615 116 633 202 633 322V398C633 491 635 533 639 561C643 600 667 614 727 617V650Z"></path></g></svg></span></td><td class="align_center">70.26</td></tr><tr><td class="align_left"><span style="width: 30.1779ptpx;"><svg height="11.9316pt" id="M73" style="vertical-align:-3.2957pt" version="1.1" viewbox="-0.0498162 -8.6359 30.1779 11.9316" width="30.1779pt" 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="M541 160L512 170C485 116 462 88 439 67C411 41 376 35 318 35C272 35 238 37 224 48C207 61 205 85 212 121L290 533C305 611 308 615 391 622L397 650H139L133 622C217 615 221 612 206 533L126 118C111 41 103 34 23 26L17 0H474C489 31 528 124 541 160Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.294,3.132)"><path d="M43 650V617C122 612 130 606 130 522V128C130 44 122 37 34 32V0H275C400 0 497 25 573 82C652 142 698 229 698 350C698 445 662 518 613 565C549 625 456 650 327 650H43ZM217 544C217 580 220 591 229 599C240 607 264 613 311 613C380 613 437 599 482 570C561 523 598 436 598 336C598 177 511 40 324 40C248 40 217 61 217 135V544Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,15,3.132)"><path d="M308 0V33C225 38 217 44 217 128V521C217 605 225 612 308 617V650H39V617C122 612 130 605 130 521V128C130 44 122 38 39 33V0H308Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,17.948,3.132)"><path d="M262 451C169 451 38 375 38 210C38 98 121 -12 261 -12C360 -12 481 64 481 227C481 351 386 451 262 451ZM249 414C337 414 385 320 385 204C385 70 333 25 272 25C189 25 134 117 134 241C134 355 189 414 249 414Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,22.671,3.132)"><path d="M727 650H480V617C552 612 575 600 580 563C583 531 587 491 587 398V326C587 153 534 44 398 44C281 44 210 124 210 296V519C210 607 218 612 298 617V650H33V617C114 609 123 607 123 519V274C123 153 151 81 211 34C258 -1 314 -14 374 -14C441 -14 509 7 556 56C615 116 633 202 633 322V398C633 491 635 533 639 561C643 600 667 614 727 617V650Z"></path></g></svg></span></td><td class="align_center">71.54</td></tr><tr><td class="align_left"><span style="width: 29.5933ptpx;"><svg height="11.9316pt" id="M74" style="vertical-align:-3.2957pt" version="1.1" viewbox="-0.0498162 -8.6359 29.5933 11.9316" width="29.5933pt" 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="M541 160L512 170C485 116 462 88 439 67C411 41 376 35 318 35C272 35 238 37 224 48C207 61 205 85 212 121L290 533C305 611 308 615 391 622L397 650H139L133 622C217 615 221 612 206 533L126 118C111 41 103 34 23 26L17 0H474C489 31 528 124 541 160Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.294,3.132)"><path d="M618 181C565 77 513 26 413 26C264 26 151 150 151 336C151 486 240 625 407 625C516 625 573 582 600 475L634 483C627 540 622 581 613 638C585 643 518 665 435 665C211 665 46 526 46 315C46 158 157 -15 406 -15C480 -15 564 4 594 12C612 43 638 121 651 168L618 181Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,14.418,3.132)"><path d="M308 0V33C225 38 217 44 217 128V521C217 605 225 612 308 617V650H39V617C122 612 130 605 130 521V128C130 44 122 38 39 33V0H308Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,17.366,3.132)"><path d="M262 451C169 451 38 375 38 210C38 98 121 -12 261 -12C360 -12 481 64 481 227C481 351 386 451 262 451ZM249 414C337 414 385 320 385 204C385 70 333 25 272 25C189 25 134 117 134 241C134 355 189 414 249 414Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,22.089,3.132)"><path d="M727 650H480V617C552 612 575 600 580 563C583 531 587 491 587 398V326C587 153 534 44 398 44C281 44 210 124 210 296V519C210 607 218 612 298 617V650H33V617C114 609 123 607 123 519V274C123 153 151 81 211 34C258 -1 314 -14 374 -14C441 -14 509 7 556 56C615 116 633 202 633 322V398C633 491 635 533 639 561C643 600 667 614 727 617V650Z"></path></g></svg></span></td><td class="align_center"><b>73.17</b></td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Computational Intelligence and Neuroscience

tab5

Table 5

Table 5: Research on Pedestrian Detection Algorithm Based on MobileNet-YoLo 