Results 21 to 30 of about 140,076 (268)
CoRR, 2016 It has long been recognized that the invariance and equivariance properties of a representation are critically important for success in many vision tasks. In this paper we present Steerable Convolutional Neural Networks, an efficient and flexible class of equivariant convolutional networks.
Taco S. Cohen, Max Welling
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Modas ocultas. Una aproximación cualitativa a fenómenos ocultistas
Vivat Academia, 2001 Desde la última guerra hay en los Estados Unidos más de treinta mil astrólogos, veinte revistas consagradas únicamente a la astrología, de las cuales una tira alrededor de los quinientos mil ejemplares.
Ana Alegre +3 more
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Stock Closing Price Prediction with Machine Learning Algorithms: PETKM Stock Example In BIST
Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2023 This study predicts the stock price of Petkim Petrokimya Holding Corp. (PETKM), which is listed in Borsa Istanbul (BIST), using PETKM stock price, US dollar (USD/TRY) price and BIST Chemical, Petroleum Plastic (XKMYA) index price.
Gültekin Çağıl +2 more
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2017 IEEE International Conference on Computer Vision (ICCV), 2017 The deep Convolutional Neural Network (CNN) is the state-of-the-art solution for large-scale visual recognition. Following basic principles such as increasing the depth and constructing highway connections, researchers have manually designed a lot of fixed network structures and verified their effectiveness. In this paper, we discuss the possibility of
Lingxi Xie, Alan L. Yuille
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CNN-based Gender Prediction in Uncontrolled Environments
Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 2021 With the increasing amount of data produced and collected, the use of artificial intelligence technologies has become inevitable. By using deep learning techniques from these technologies, high performance can be achieved in tasks such as classification ...
Kazım Yıldız, Engin Güneş, Anil Bas
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A Deep Learning Approach for DDoS Attack Detection Using Supervised Learning [PDF]
MATEC Web of Conferences, 2021 This research presents a novel combined learning method for developing a novel DDoS model that is expandable and flexible property of deep learning. This method can advance the current practice and problems in DDoS detection.
Tekleselassie Hailye
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CNN+CNN: Convolutional Decoders for Image Captioning
CoRR, 2018 Image captioning is a challenging task that combines the field of computer vision and natural language processing. A variety of approaches have been proposed to achieve the goal of automatically describing an image, and recurrent neural network (RNN) or long-short term memory (LSTM) based models dominate this field.
Qingzhong Wang, Antoni B. Chan
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Deep Learning Method for Multi-Attribute Analysis of Fingerprint Images [PDF]
Computer Science Journal of MoldovaEstimation of gender, hand, and finger to minimize the probable suspects list in a fingerprint database search is a very important stride in forensic anthropology. Previous research attempted to estimate the gender, hand, and finger from the fingerprint,
Diptadip Maiti +2 more
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Successive Image Generation from a Single Sentence [PDF]
ITM Web of Conferences, 2021 Through various examples in history such as the early man’s carving on caves, dependence on diagrammatic representations, the immense popularity of comic books we have seen that vision has a higher reach in communication than written words. In this paper,
Parab Amogh +4 more
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Design of vocieprint recognition system based on CNN-LSTM neural network
Dianzi Jishu Yingyong, 2021 For warning of cardiovascular disease,in order to early detect the change of heart and lung voice representing the signs of danger,the vocieprint recognition system based on CNN-LSTM is designed.
Mu Junjie, Yao Gang, Sun Tao
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