Results 31 to 40 of about 530,080 (274)
Dimensionality Reduction of Deep Learning for Earth Observation: Smaller, Faster, Simpler
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 As deep learning attracts earth observation (EO) community's interest, the challenge to derive explainable, actionable information creates a bottleneck in EO models' development.
Iulia Calota, Daniela Faur, Mihai Datcu
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Kluster Bag of Word Menggunakan Weka
Jurnal Edukasi dan Penelitian Informatika (JEPIN), 2015 Dalam bidang pengolahan bahasa alami dan sistem temu balik informasi, representasi sebuah data teks sangat penting untuk mendukung proses analisis data statistik di dalamnya. Data teks dengan bentuk tidak terstruktur dapat direpresentasikan secara sederhana menggunakan sekumpulan set kata yang disebut bag-of-words dan belum memiliki label atau kelas ...
Tari Mardiana, Rudy Dwi Nyoto
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Investigating the Bag-of-Words Method for 3D Shape Retrieval
EURASIP Journal on Advances in Signal Processing, 2010 This paper investigates the capabilities of the Bag-of-Words (BWs) method in the 3D shape retrieval field. The contributions of this paper are (1) the 3D shape retrieval task is categorized from different points of view: specific versus generic, partial ...
Afzal Godil, Xiaolan Li
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Bag of Words and Embedding Text Representation Methods for Medical Article Classification
International Journal of Applied Mathematics and Computer Science, 2023 Text classification has become a standard component of automated systematic literature review (SLR) solutions, where articles are classified as relevant or irrelevant to a particular literature study topic.
Cichosz Paweł
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Video matching method based on "bag of words"
Tongxin xuebao, 2007 A "bag of words" was presented based method for video representation and matching.First,all local features of all video frames were quantized into a dictionary of visual words.Then each sub-shot of the video was represented by a set of visual words ...
LI Yuan-ning1 +3 more
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Dissimilarities Detections in Texts Using Symbol n-grams and Word Histograms
Open Computer Science, 2016 Texts (books, novels, papers, short messages) are sequences of sentences, words or symbols. Each author has an unique writing style. It can be characterized by some collection of attributes obtained from texts.
Andrejková Gabriela +1 more
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Learning Word Importance with the Neural Bag-of-Words Model [PDF]
Proceedings of the 1st Workshop on Representation Learning for NLP, 2016 The Neural Bag-of-Words (NBOW) modelperforms classification with an average ofthe input word vectors and achieves an impressiveperformance. While the NBOWmodel learns word vectors targeted forthe classification task it does not explicitlymodel which words are important forgiven task.
Sheikh, Imran +3 more
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Pruning the vocabulary for better context recognition [PDF]
, 2004 Language independent `bag-of-words' representations are surprisingly effective for text classification. The representation is high dimensional though, containing many nonconsistent words for text categorization.
Hansen, Lars Kai +3 more
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Softening quantization in bag-of-audio-words [PDF]
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014 The audio component of multimedia data can be crucial for multimedia content analysis. Bag-of-audio-words (BoAW) approach is one of the most frequently used methods to represent audio content in multimedia event detection and related tasks. The method, however, has numerous criticisms, amongst which is the loss of information in the “vector ...
Stephanie Pancoast, Murat Akbacak
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Enriching basic features via multilayer bag-of-words binding for Chinese question classification
CAAI Transactions on Intelligence Technology, 2019 Question classification helps to generate more accurate answers in question answering system. For an efficient question classifier, one of the most important tasks is to fully mine useful features.
Sichun Yang, Chao Gao
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