000			02697nam a2200337Ia 4500
000			03249nam a22003615i 4500
001			978-981-99-0279-8
003			DE-He213
005			20240319120907.0
007			cr nn 008mamaa
008			230330s2023 si | s |||| 0|eng d
020			_a9789819902798 _9978-981-99-0279-8
082			_a6.37
100			_aHuang, Yan. _931805
245			_aDeep Cognitive Networks _cby Yan Huang, Liang Wang. _h[electronic resource] :
250			_a1st ed. 2023.
260			_aSingapore _bSpringer Nature Singapore _c2023
300			_aX, 62 p. 1 illus. _bonline resource.
520			_aAlthough deep learning models have achieved great progress in vision, speech, language, planning, control, and many other areas, there still exists a large performance gap between deep learning models and the human cognitive system. Many researchers argue that one of the major reasons accounting for the performance gap is that deep learning models and the human cognitive system process visual information in very different ways. To mimic the performance gap, since 2014, there has been a trend to model various cognitive mechanisms from cognitive neuroscience, e.g., attention, memory, reasoning, and decision, based on deep learning models. This book unifies these new kinds of deep learning models and calls them deep cognitive networks, which model various human cognitive mechanisms based on deep learning models. As a result, various cognitive functions are implemented, e.g., selective extraction, knowledge reuse, and problem solving, for more effective information processing. This book first summarizes existing evidence of human cognitive mechanism modeling from cognitive psychology and proposes a general framework of deep cognitive networks that jointly considers multiple cognitive mechanisms. Then, it analyzes related works and focuses primarily but not exclusively, on the taxonomy of four key cognitive mechanisms (i.e., attention, memory, reasoning, and decision) surrounding deep cognitive networks. Finally, this book studies two representative cases of applying deep cognitive networks to the task of image-text matching and discusses important future directions.
650			_aArtificial intelligence. _931806
650			_aArtificial Intelligence. _931807
650			_aComputer Imaging, Vision, Pattern Recognition and Graphics. _931808
650			_aComputer vision. _931809
650			_aComputer Vision. _931810
650			_aImage processing _931811
650			_aImage processing. _931811
650			_aImage Processing. _931812
700			_aWang, Liang. _931813
856			_uhttps://doi.org/10.1007/978-981-99-0279-8
942			_cEBK _2ddc
999			_c15245 _d15245