全文获取类型
收费全文 | 4492篇 |
免费 | 386篇 |
国内免费 | 544篇 |
出版年
2024年 | 7篇 |
2023年 | 94篇 |
2022年 | 132篇 |
2021年 | 223篇 |
2020年 | 226篇 |
2019年 | 228篇 |
2018年 | 217篇 |
2017年 | 253篇 |
2016年 | 262篇 |
2015年 | 196篇 |
2014年 | 261篇 |
2013年 | 707篇 |
2012年 | 156篇 |
2011年 | 252篇 |
2010年 | 189篇 |
2009年 | 268篇 |
2008年 | 274篇 |
2007年 | 241篇 |
2006年 | 195篇 |
2005年 | 162篇 |
2004年 | 144篇 |
2003年 | 132篇 |
2002年 | 105篇 |
2001年 | 65篇 |
2000年 | 62篇 |
1999年 | 44篇 |
1998年 | 27篇 |
1997年 | 42篇 |
1996年 | 29篇 |
1995年 | 27篇 |
1994年 | 20篇 |
1993年 | 19篇 |
1992年 | 20篇 |
1991年 | 7篇 |
1990年 | 12篇 |
1989年 | 13篇 |
1988年 | 9篇 |
1987年 | 11篇 |
1986年 | 8篇 |
1985年 | 9篇 |
1984年 | 10篇 |
1983年 | 14篇 |
1982年 | 8篇 |
1981年 | 6篇 |
1980年 | 6篇 |
1979年 | 6篇 |
1978年 | 12篇 |
1977年 | 6篇 |
1976年 | 3篇 |
1973年 | 2篇 |
排序方式: 共有5422条查询结果,搜索用时 31 毫秒
91.
Advances in applying statistical Machine Learning (ML) led to several claims of human-level or near-human performance in tasks such as image classification & speech recognition. Such claims are unscientific primarily for two reasons, (1) They incorrectly enforce the notion that task-specific performance can be treated as manifestation of General Intelligence and (2) They are not verifiable as currently there is no set benchmark for measuring human-like cognition in a machine learning agent. Moreover, ML agent’s performance is influenced by knowledge ingested in it by its human designers. Therefore, agent’s performance may not necessarily reflect its true cognition. In this paper, we propose a framework that draws parallels from human cognition to measure machine’s cognition. Human cognitive learning is quite well studied in developmental psychology with frameworks and metrics in place to measure actual learning. To either believe or refute the claims of human-level performance of machine learning agent, we need scientific methodology to measure its cognition. Our framework formalizes incremental implementation of human-like cognitive processes in ML agents with an implicit goal to measure it. The framework offers guiding principles for measuring, (1) Task-specific machine cognition and (2) General machine cognition that spans across tasks. The framework also provides guidelines for building domain-specific task taxonomies to cognitively profile tasks. We demonstrate application of the framework with a case study where two ML agents that perform Vision and NLP tasks are cognitively evaluated. 相似文献
92.
Learning processes can be described by adaptive mental (or neural) network models. If metacognition is used to regulate learning, the adaptation of the mental network becomes itself adaptive as well: second-order adaptation. In this paper, a second-order adaptive mental network model is introduced for metacognitive regulation of learning processes. The focus is on the role of multiple internal mental models, in particular, the case of visualisation to support learning of numerical or symbolic skills. The second-order adaptive network model is illustrated by a case scenario for the role of visualisation to support learning multiplication at the primary school. 相似文献
93.
Under numerous circumstances, humans recognize visual objects in their environment with remarkable response times and accuracy. Existing artificial visual object recognition systems have not yet surpassed human vision, especially in its universality of application. We argue that modeling the recognition process in an exclusive feedforward manner hinders those systems’ performance. To bridge that performance gap between them and human vision, we present a brief review of neuroscientific data, which suggests that considering an agent’s internal influences (from cognitive systems that peripherally interact with visual-perceptual processes) recognition can be improved. Then, we propose a model for visual object recognition which uses these systems’ information, such as affection, for generating expectation to prime the object recognition system, thus reducing its execution times. Later, an implementation of the model is described. Finally, we present and discuss an experiment and its results. 相似文献
94.
Every person, from an early age, has to make decisions to resolve situations that arise in life. In general, different people make different decisions in the same situation, since decision-making takes into account different factors such as age, emotional state, experience, among others. We can make decisions about situations that we classify as: more important than others, routine, unexpected, or trivial. However, making the correct decision(s) in a timely manner for these situations is one of the most complex and delicate challenges that human beings face. This is due to the arduous mental process required to be carried out. Providing such behavior to a virtual entity is possible through the use of Cognitive Architectures (CAs). CAs are an approach for modeling human intelligence and behavior. This paper presents an functional bioinspired computational decision-making model to satisfy the physiological needs of hunger and thirst. Our proposal considers as black boxes other cognitive functions that are part of a general CA (named Cuäyöllötl or brain in Nahuatl). In the proposed case study, it is proved that the decision-making process plays an essential role in determining the objective and selecting the object that satisfies the established need. 相似文献
95.
Memory is considered one of the most important functions since it allows us to code, store and retrieve knowledge. These qualities make it an indispensable function for a virtual creature. In general, memory can be classified based on the durability of the stored data in working memory and long-term memory. Working memory refers to the capacity to maintain temporarily a limited amount of information in mind, which can then be used to support various abilities, including learning, reasoning, planning and decision-making. Unlike short-term memory, working memory is not only a storage site, but it is also a framework of interacting processes that involve the temporary storage and manipulation of information in the service of performing complex cognitive activities. Declarative memory is a type of long-term memory related with the storage of facts and events. This research focuses on the development of a cognitive architecture for the type of working memory that maintains and manipulates declarative information. The construction of the model was grounded in theoretical evidence taken from cognitive sciences such as neuroscience and psychology, which gave us the components and their processes. The model was evaluated through a case study that covers the encoding, storing, and retrieval stages. Our hypothesis is that a virtual creature endowed with our working memory model will provide faster access to the information needed for the ongoing task. Therefore, it improves the planning and decision-making processes. 相似文献
96.
In this work, we attempted to find out the relationship between different gait patterns and their corresponding cognitive states by using different statistical and machine learning approaches. This paper strongly focusses on the simulations followed by implementation of the proposed cognitive states i.e. (i) EmotionOriented State (EOS) (ii) Thinking Oriented State (TOS) (iii) Memory Oriented State(MOS) (iv) Simple Regular Oriented State (SROS). A novel approach was implemented by creating different environmental contexts for different gaits in our lab. An experimental method was performed to isolate movement artifact using Independent Component Analysis from recorded EEG(Electroencephalogram) signals. Measurement of joint angles from joint positions captured using Kinect V2 sensors was done with the help of OpenSim software. The relationship between different gaits and mental states was established using Pearsons Correlation Coefficient, ANOVA(Analysis of variance) and SVM(Support Vector Machine) classifier respectively. A strong relationship was found between them. The SVM classifier for the EOS and the non-EOS states based on joint angles inferred an accuracy of 81.08%. The ROC Curve for SVM classification depicted an AUC (area under the curve) of 0.9724. 相似文献
97.
审美对象特有的刺激属性会唤起观赏者特定的情绪或情感反应。个体在欣赏自然、艺术品和其他人类作品时会产生审美愉悦体验。审美愉悦-兴趣模型(PIA)认为, 审美愉悦体验包含审美过程中自动化加工阶段的审美愉悦和控制加工阶段的审美兴趣。近年来, 神经美学研究表明, 负责愉悦和奖赏的眶额叶皮层在审美过程中广泛激活, 是自动化加工阶段初级审美愉悦奖赏的神经基础, 而审美过程中纹状体亚回路中不同的连接和功能作用与两个阶段中审美愉悦的产生都有关联; 上述结果支持了审美愉悦-兴趣模型。但审美高峰体验时默认模式网络(DMN)相关脑区的激活和负责控制与理性思维的外侧前额叶皮层等脑区的失活, 提示在PIA模型强调的自动化加工阶段审美愉悦和控制加工阶段审美兴趣之上, 还有整合升华阶段的审美沉浸愉悦, PIA模型需得到进一步的扩展。未来研究应进一步检验审美愉悦认知加工模型及神经机制, 探索审美对创造力的影响机制和神经基础, 探讨不同审美经验愉悦机制的异同。 相似文献
98.
认知诊断评估旨在探讨个体内部的知识掌握结构,并提供关于学生优缺点的详细诊断信息,以促进个体的全面发展。当前研究者已开发了大量0-1评分的认知诊断模型,但对于多级评分认知诊断模型的研究还比较少。本文对已有的多级评分认知诊断模型进行了归纳,介绍了模型的假设,计量特征以及适用范围,为实际应用者和研究者在多级评分认知诊断模型的比较和选用上提供借鉴和参考。最后,对未来关于多级评分诊断模型的研究方向进行了展望。 相似文献
99.
不断加剧的经济不平等问题对个体和社会有着巨大危害,然而人们对经济不平等却有着较高的容忍性。基于个体心理的研究证据,本文提出认知和动机双重路径模型来解释个体容忍和支持经济不平等问题。在认知路径上,个体倾向于低估当前社会的经济不平等程度和将经济不平等评价为公平的;在动机路径上,个体预期经济不平等将带来自我利益的增加。未来研究应进一步整合多重心理机制间的关系,并探索有效干预手段以增加人们对减少经济不平等的支持。 相似文献
100.