Low-Shot Wall Defect Detection for Autonomous Decoration Robots Using Deep Reinforcement Learning

<div>The input parameters of inner LSTM. 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394L329 433Z"></path></g></svg>,</span> and its update is <span class="nowrap"><svg height="12.7178pt" id="M29" style="vertical-align:-3.42947pt" version="1.1" viewbox="-0.0498162 -9.28833 98.7563 12.7178" width="98.7563pt" 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="M499 88L487 113C459 86 422 65 413 65C403 65 403 74 409 98L461 318C487 426 460 448 431 448C408 448 383 441 352 424C305 398 223 344 157 257H155L243 674C249 702 249 712 240 712C227 712 170 680 87 673L82 648H117C155 648 162 644 150 590L23 -4L30 -12C55 -4 81 3 105 8C113 53 131 150 143 187C199 281 323 387 372 387C390 387 393 369 380 311L328 86C313 19 319 -12 347 -12C379 -12 442 24 499 88Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,6.643,3.132)"><path d="M329 433H203L239 587L230 596L147 534L123 433H57L30 395L34 388H115L61 129C37 16 59 -12 85 -12C147 -12 222 58 260 98L241 125C212 95 160 62 144 62C132 62 127 71 138 126L192 386L305 394L329 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Journal of Robotics

fig5

Figure 5

Figure 5: Low-Shot Wall Defect Detection for Autonomous Decoration Robots Using Deep Reinforcement Learning 