Pub Date : 2020-10-01 DOI:10.4018/ijiit.2020100104
Aahan Singh, N. Nagaraj, Srinidhi Hiriyannaiah, L. Patnaik
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引用次数: 2

摘要

人工智能为不同的计算领域铺平了道路,如语音识别和翻译、对象检测、机器翻译等。人工通用智能的目标之一是在机器中模拟人类的思维和理性,使它们能够感知环境,然后根据自己的感知执行合理的行动。创建一个单一的模型来执行从视觉感知到驱动的每一个任务目前是不可能的。系统必须分为几个模型,每个模型都独立运行,也有助于整个智能机器的运行。本文提出了一种能够检测图像中生物/非生物物体及其运动状态的智能传感和字幕生成(ISCG)系统。该系统由两个独立的模块组成:标题生成器和智能引擎,其中卷积神经网络(CNN)用于确定图像中的不同物体。我们的模型在基准数据集上产生最先进的性能。
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ISCG
Artificial intelligence has paved the way for different areas of computing such as speech recognition and translation, object detection, machine translation, and others. One of the goals of artificial general intelligence is to simulate human thinking and rationality within machines such that they are able to perceive their environment and then perform reasonable actions based on their perception. Creating a single model that performs every single task from visual perception to actuation is currently impossible. The system must be divided into several models each of which functions independently as well also contribute to the operation of the whole intelligent machine. In this paper, an intelligent sensing and caption generation (ISCG) system is proposed which is capable of detecting living/non-living objects and states of motion in images. The system consists of two separate modules of caption generator and intelligence engine with a Convolutional Neural Network (CNN) for determining the different objects in the images. Our model yields state-of-the-art performance on benchmarked dataset.
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