“深文”如何浅教

对初中学生来说 ,“深文”必须浅教。如何浅教 ?笔者教学实践的经验体会是 :定位要“准”,导入要“巧”,诵读要“实”,品析要“活”,迁移要“新”。

End-to-end dilated convolution network for document image semantic segmentation

Semantic segmentation is a crucial step for document understanding.In this paper,an NVIDIA Jetson Nano-based platform is applied for implementing semantic segmentation for teaching artificial intelligence concepts and programming.To extract semantic structures from document images,we present an end-to-end dilated convolution network architecture.Dilated convolutions have well-known advantages for extracting multi-scale context information without losing spatial resolution.Our model utilizes dilated convolutions with residual network to represent the image features and predicting pixel labels.The convolution part works as feature extractor to obtain multidimensional and hierarchical image features.The consecutive deconvolution is used for producing full resolution segmentation prediction.The probability of each pixel decides its predefined semantic class label.To understand segmentation granularity,we compare performances at three different levels.From fine grained class to coarse class levels,the proposed dilated convolution network architecture is evaluated on three document datasets.The experimental results have shown that both semantic data distribution imbalance and network depth are import factors that influence the document’s semantic segmentation performances.The research is aimed at offering an education resource for teaching artificial intelligence concepts and techniques.

A Hybrid Method of Extractive Text Summarization Based on Deep Learning and Graph Ranking Algorithms

In the era of Big Data,we are faced with an inevitable and challenging problem of“overload information”.To alleviate this problem,it is important to use effective automatic text summarization techniques to obtain the key information quickly and efficiently from the huge amount of text.In this paper,we propose a hybrid method of extractive text summarization based on deep learning and graph ranking algorithms(ETSDG).In this method,a pre-trained deep learning model is designed to yield useful sentence embeddings.Given the association between sentences in raw documents,a traditional LexRank algorithm with fine-tuning is adopted fin ETSDG.In order to improve the performance of the extractive text summarization method,we further integrate the traditional LexRank algorithm with deep learning.Testing results on the data set DUC2004 show that ETSDG has better performance in ROUGE metrics compared with certain benchmark methods.

A deep dense captioning framework with joint localization and contextual reasoning

Dense captioning aims to simultaneously localize and describe regions-of-interest(RoIs)in images in natural language.Specifically,we identify three key problems:1)dense and highly overlapping RoIs,making accurate localization of each target region challenging;2)some visually ambiguous target regions which are hard to recognize each of them just by appearance;3)an extremely deep image representation which is of central importance for visual recognition.To tackle these three challenges,we propose a novel end-to-end dense captioning framework consisting of a joint localization module,a contextual reasoning module and a deep convolutional neural network(CNN).We also evaluate five deep CNN structures to explore the benefits of each.Extensive experiments on visual genome(VG)dataset demonstrate the effectiveness of our approach,which compares favorably with the state-of-the-art methods.

Acupuncture analgesia and the direction,angle and depth of needle insertion

Literatures on acupuncture analgesia of the recent 30 years are analyzed through the target pain syndromes, points and tools selected for needling as well as the chosen direction, angle and depth of insertion. The relationship between effect of acupuncture analgesia and needling direction, angle as well as depth is initially optimized to enhance the analgesic effect. The result shows that the 3 factors are the key influences. However, studies on the above mentioned relation are still far from enough. Aiming at enhancing the effect of acupuncture analgesia and exploring the relative mechanism, it is held that multivariate analysis should be adopted to do systematic analysis on relationship between effect and mechanism of acupuncture analgesia and direction, angle and depth of the needle insertion.