[ { "text": "The Long Short-Term Memory", "score": 0.9994322657585144, "polygon": [ [ 32.0, 24.0 ], [ 543.0, 30.0 ], [ 543.0, 65.0 ], [ 32.0, 60.0 ] ] }, { "text": " LSTM networks learns long-term dependencies better", "score": 0.9935519099235535, "polygon": [ [ 120.0, 268.0 ], [ 823.0, 269.0 ], [ 823.0, 294.0 ], [ 120.0, 292.0 ] ] }, { "text": " Optimization", "score": 0.9938980340957642, "polygon": [ [ 119.0, 316.0 ], [ 311.0, 316.0 ], [ 311.0, 343.0 ], [ 119.0, 343.0 ] ] }, { "text": ": Clipping gradient", "score": 0.9587327837944031, "polygon": [ [ 180.0, 364.0 ], [ 406.0, 364.0 ], [ 406.0, 385.0 ], [ 180.0, 385.0 ] ] }, { "text": ". Regularizing: encourage information flow", "score": 0.9854925870895386, "polygon": [ [ 177.0, 399.0 ], [ 685.0, 400.0 ], [ 685.0, 428.0 ], [ 177.0, 427.0 ] ] }, { "text": ". Case studies:", "score": 0.8947544693946838, "polygon": [ [ 119.0, 446.0 ], [ 311.0, 448.0 ], [ 311.0, 472.0 ], [ 119.0, 470.0 ] ] }, { "text": " Memory networks (Westion et al., 2014)", "score": 0.9780460000038147, "polygon": [ [ 181.0, 494.0 ], [ 681.0, 494.0 ], [ 681.0, 518.0 ], [ 181.0, 518.0 ] ] }, { "text": " Neural Turing machine (Graves et al., 2014)", "score": 0.9989622235298157, "polygon": [ [ 181.0, 532.0 ], [ 727.0, 532.0 ], [ 727.0, 557.0 ], [ 181.0, 557.0 ] ] }, { "text": " Multiple object recognition with attention (Ba et al.)", "score": 0.9943037629127502, "polygon": [ [ 182.0, 569.0 ], [ 830.0, 571.0 ], [ 830.0, 595.0 ], [ 182.0, 593.0 ] ] }, { "text": ": Image captioning", "score": 0.97649085521698, "polygon": [ [ 181.0, 604.0 ], [ 409.0, 610.0 ], [ 408.0, 638.0 ], [ 180.0, 633.0 ] ] }, { "text": "ecturer: Duc Dung Nguyen, PhD. Contact: nddung@hcmut.edu.vn", "score": 0.9703457951545715, "polygon": [ [ 50.0, 761.0 ], [ 506.0, 761.0 ], [ 506.0, 775.0 ], [ 50.0, 775.0 ] ] }, { "text": "Deep Learning", "score": 0.996578574180603, "polygon": [ [ 765.0, 758.0 ], [ 864.0, 760.0 ], [ 864.0, 778.0 ], [ 764.0, 776.0 ] ] }, { "text": "47/ 47", "score": 0.9623189568519592, "polygon": [ [ 1120.0, 759.0 ], [ 1175.0, 759.0 ], [ 1175.0, 777.0 ], [ 1120.0, 777.0 ] ] } ]