Social media is a very important tool in this modern era , one of which namely twitter. Twitter allows user for give opinion / to various issues and topics hot viral trending . Trending on twitter so fast the process spreading that becomes medium information often become issue conspiracy Covid-19 moderate epidemic disease _ experienced whole world when Issues circulating population they believe...

Scene labeling is a challenging computer vision task. It requires the use of both local discriminative features and global context information. We adopt a deep recurrent convolutional neural network (RCNN) for this task, which is originally proposed for object recognition. Different from traditional convolutional neural networks (CNN), this model has intra-layer recurrent connections in the con...

Convolutional Neural Network (CNN) was firstly introduced in Computer Vision for image recognition by LeCun et al. in 1989. Since then, it has been widely used in image recognition and classification tasks. The recent impressive success of Krizhevsky et al. in ILSVRC 2012 competition demonstrates the significant advance of modern deep CNN on image classification task. Inspired by his work, many...

In sentence modeling and classification, convolutional neural network approaches have recently achieved state-of-the-art results, but all such efforts process word vectors sequentially and neglect long-distance dependencies. To exploit both deep learning and linguistic structures, we propose a tree-based convolutional neural network model which exploit various long-distance relationships betwee...

We introduce a convolutional neural network for inferring a compact disentangled graphical description of objects from 2D images that can be used for volumetric reconstruction. The network comprises an encoder and a twin-tailed decoder. The encoder generates a disentangled graphics code. The first decoder generates a volume, and the second decoder reconstructs the input image using a novel trai...

根據神經生理學研究,耳朵會針對聲音的各個頻率進行分頻,並產生出聽覺頻譜,研究人 員根據專注聽覺現象和生物聽覺實驗,也發現了大腦聽覺皮質上神經作用的模式。於本論文中, 我們運用類神經網路,建構出一種模擬人類聽覺的類神經網路模型,並在語者識別這個應用上 進行討論,期望能成功連結神經生理學的知識與工程的技術。而我們所設計的模型,是利用兩 層不同維度的卷積神經網路(Convolutional Neural Network),分別模擬初期耳蝸階段及大腦皮質 階段,透過設計卷積核初始值,即耳蝸階段多組一維分頻濾波器和大腦皮質階段同時解析時頻 資訊的二維濾波器,以使模型能夠快速地達到收斂狀態。而透過模型訓練,根據目的與環境變 因的不同,模型會自動調整其中參數,使輸入資料映射至目標的型態。同時我們也針對所提出 的模型架構,進行了多種形態的比較,進而發現在給定初始值的狀況下,即使訓練不夠充分, 也能產...

Augmenting X-ray imaging with 3D roadmap to improve guidance is a common strategy. Such approaches benefit from automated analysis of the X-ray images, such as the automatic detection and tracking of instruments. In this paper, we propose a real-time method to segment the catheter and guidewire in 2D X-ray fluoroscopic sequences. The method is based on deep convolutional neural networks. The ne...

Music genre classification is one example of content-based analysis of music signals. Traditionally, human engineered features were used to automatize this task and 61% accuracy has been achieved in the 10-genre classification. However, it’s still below the 70% accuracy that humans could achieve in the same task. Here, we propose a new method that combines knowledge of human perception study in...

Lung nodule classification is a class imbalanced problem, as nodules are found with much lower frequency than non-nodules. In the class imbalanced problem, conventional classifiers tend to be overwhelmed by the majority class and ignore the minority class. We showed that cascaded convolutional neural networks can classify the nodule candidates precisely for a class imbalanced nodule candidate d...

This paper describes our participation at the LifeCLEF Fish task 2015. The task is about video-based fish identification. Firstly, we applied foreground detection method with selective search to extract candidate fish object window. Then deep convolutional neural network is used to classify fish species per window. Classification results are post-processed to produce final identification output...