Internet CNN NEWSROOM is a digital video news magazine based on content from CNN NEWSROOM, an educational news program produced by Turner Educational Services, Inc. Internet CNN NEWSROOM is automatically generated and distributed each day. Internet CNN NEWSROOM uses MPEG digital video and is distributed via the World Wide Web on the Internet. This thesis describes the design and development of ...

Description: Statistical approaches to early vision processes need a huge amount of computing power. These algorithms can usually be implemented on parallel computing structures. With the Cellular Neural Networks [9] (CNN), a new image processing tool is coming into consideration. Its VLSI implementation takes place on a single analog chip containing several thousands (recently about 10,000 to ...

Convolutional Neural Network (NN) has gained a lot of attention of the researchers due to its high accuracy in classification and feature learning. In this paper, we evaluated the performance of CNN used as feature for image retrieval with the gold standard feature, aka SIFT. Experiments are conducted on famous Oxford 5k data-set. The mAP of SIFT and CNN is 0.6279 and 0.5284, respectively. The ...

Individual identification is a basic requirement for research in behavior, ecology and conservation. Photographic records are commonly used situations where individuals visually distinct. However, keeping track of identities becomes challenging with increasing population sizes corresponding datasets. There growing interest the potential deep-learning methods computer vision to assist automating...

Internet CNN NEWSROOM is a digital video news magazine based on content from CNN NEWSROOM, an educational news program produced by Turner Educational Services, Inc. Internet CNN NEWSROOM is automatically generated and distributed each day. Internet CNN NEWSROOM uses MPEG digital video and is distributed via the World Wide Web on the Internet. This thesis describes the design and development of ...

Description: Statistical approaches to early vision processes need a huge amount of computing power. These algorithms can usually be implemented on parallel computing structures. With the Cellular Neural Networks [9] (CNN), a new image processing tool is coming into consideration. Its VLSI implementation takes place on a single analog chip containing several thousands (recently about 10,000 to ...

Description: Statistical approaches to early vision processes need a huge amount of computing power. These algorithms can usually be implemented on parallel computing structures. With the Cellular Neural Networks [9] (CNN), a new image processing tool is coming into consideration. Its VLSI implementation takes place on a single analog chip containing several thousands (recently about 10,000 to ...

Description: Statistical approaches to early vision processes need a huge amount of computing power. These algorithms can usually be implemented on parallel computing structures. With the Cellular Neural Networks [9] (CNN), a new image processing tool is coming into consideration. Its VLSI implementation takes place on a single analog chip containing several thousands (recently about 10,000 to ...

The automatic character recognition of historic documents gained more attention from scholars recently, due to the big improvements in computer vision, image processing, and digitization. While Neural Networks, current state-of-the-art models used for recognition, are very performant, they typically suffer using large amounts training data. In our study we manually built own relatively small da...

Convolution Neural Networks (CNNs) are widely deployed in computer vision applications. The datasets large, and the data reuse across different parts is heavily interleaved. Given that memory access (SRAM especially DRAM) more expensive both performance energy than computation, maximizing to reduce movement hierarchy critical improving execution efficiency. This even important for common use ca...