کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6941084 | 870212 | 2015 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Factored four way conditional restricted Boltzmann machines for activity recognition
ترجمه فارسی عنوان
ماشین های بولتزمن برای تشخیص فعالیت های محدود چهارطرفه ثابت شده
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
This paper introduces a new learning algorithm for human activity recognition capable of simultaneous regression and classification. Building upon conditional restricted Boltzmann machines (CRBMs), Factored four way conditional restricted Boltzmann machines (FFW-CRBMs) incorporate a new label layer and four-way interactions among the neurons from the different layers. The additional layer gives the classification nodes a similar strong multiplicative effect compared to the other layers, and avoids that the classification neurons are overwhelmed by the (much larger set of) other neurons. This makes FFW-CRBMs capable of performing activity recognition, prediction and self auto evaluation of classification within one unified framework. As a second contribution, sequential Markov chain contrastive divergence (SMcCD) is introduced. SMcCD modifies Contrastive Divergence to compensate for the extra complexity of FFW-CRBMs during training. Two sets of experiments one on benchmark datasets and one a robotic platform for smart companions show the effectiveness of FFW-CRBMs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 66, 15 November 2015, Pages 100-108
Journal: Pattern Recognition Letters - Volume 66, 15 November 2015, Pages 100-108
نویسندگان
Decebal Constantin Mocanu, Haitham Bou Ammar, Dietwig Lowet, Kurt Driessens, Antonio Liotta, Gerhard Weiss, Karl Tuyls,