3D TARGET DETECTION USING STACKED HOLOGRAM

Fast Hologram Synthesis for 3D Geometry Models using Graphics Hardware

The holographic visualization of three-dimensional object geometry still represents a major challenge in computational holography research. Besides the development of suitable holographic display devices, the fast calculation of the hologram’s interference pattern for complex-shaped three-dimensional objects is an important pre-requisite of any interactive holographic display system. We present...

Disfluency Detection Using Multi-step Stacked Learning

In this paper, we propose a multi-step stacked learning model for disfluency detection. Our method incorporates refined n-gram features step by step from different word sequences. First, we detect filler words. Second, edited words are detected using n-gram features extracted from both the original text and filler filtered text. In the third step, additional n-gram features are extracted from e...

3D Hologram Technology in Learning Environment

Major progress has taken place in the field of ICT usage in learning environments. The advantages offered by ICT in this sector have led most educational institutions to integrate ICT services into their departments. Scientists are working very hard to provide an advanced technology, which can benefit them in many areas. 3D Hologram Technology (3DHT) is one of the most creative of these solutio...

Detection of Congenital Mullerian Anomalies Using Real-Time 3D Sonography

Source-Target-Source Classification Using Stacked Denoising Autoencoders

Deep Transfer Learning (DTL) emerged as a new paradigm in machine learning in which a deep model is trained on a source task and the knowledge acquired is then totally or partially transferred to help in solving a target task. Even though DTL offers a greater flexibility in extracting high-level features and enabling feature transference from a source to a target task, the DTL solution might ge...