Automatic image caption prediction is a challenging task in natural language processing. Most of the researchers have used convolutional neural network as an encoder and decoder. However, accurate requires model to understand semantic relationship that exists between various objects present image. The attention mechanism performs linear combination decoder states. It emphasizes information with...

Weakly supervised semantic segmentation (WSSS) methods have received significant attention in recent years, since they can dramatically reduce the annotation costs of fully alternatives. While most previous studies focused on leveraging classification labels, we explore instead use image captions, which be obtained easily from web and contain richer visual information. Existing for this task as...

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This study aims to develop a hybridized deep learning model for generating semantically meaningful image captions in Amharic Language. Image captioning is task that combines both computer vision and natural language processing (NLP) domains. However, existing studies the English primarily focus on visual features generate captions, resulting gap between textual inadequate semantic representatio...

We present IntoNews, a system to match online news articles with spoken news from a television newscasts represented by closed captions. We formalize the news matching problem as two independent tasks: closed captions segmentation and news retrieval. The system segments closed captions by using a windowing scheme: sliding or tumbling window. Next, it uses each segment to build a query by extrac...

Automatic indexing to image data is in strong demand. Utilizing accompanying natural language information is considered e ective to accomplish the task. As a basis for semantic indexing, we propose an automatic television caption semantic analysis method, which analyzes semantic attributes of Japanese television news captions referring to su xes. This is a basic pre-process required to enable a...

Closed captioning dramatically improves deaf people's enjoyment of television shows, and appears to augment the auditory signal for people with some degree of hearing impairment. However, reports from people with mild to severe hearing loss suggest that when there is a delay between the audio track and the caption, perceivers are confused unless they turn down the volume. These effects have not...

Image captioning using deep neural networks has recently gained increasing attention, mostly for English langue, with only few studies in other languages. Good image model is required to automatically generate sensible, syntactically and semantically correct captions, which turn requires good models both computer vision natural language processing. The process more challenging case of data scar...