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Refinado por: tipo de recurso: Anais de Congresso remover
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Automation animal tracker using complex value neural network
Automation animal tracker using complex value neural network
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Automation animal tracker using complex value neural network

Imah, Elly Matul ; Wintarti, Atik ; Sulaiman, R. ; Manuharawati, Manuharawati Abdullah, Ade Gafar ; Nandiyanto, Asep Bayu Dani

MATEC Web of Conferences, 2018, Vol.197, p.3020 [Periódico revisado por pares]

Les Ulis: EDP Sciences

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12
A tracking system for laboratory mice to support medical researchers in behavioral analysis
A tracking system for laboratory mice to support medical researchers in behavioral analysis
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A tracking system for laboratory mice to support medical researchers in behavioral analysis

Macri, S. ; Mainetti, L. ; Patrono, L. ; Pieretti, S. ; Secco, A. ; Sergi, I.

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015, p.4946-4949

IEEE

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13
Human animal machine interaction: animal behavior awareness and digital experience
Human animal machine interaction: animal behavior awareness and digital experience
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Human animal machine interaction: animal behavior awareness and digital experience

Fahlquist, Karin ; Karlsson, Johannes ; Li, Haibo ; Liu, Li ; Ren, Keni ; ur Réhman, Shafiq ; Wark, Tim

Digital Djurpark, 2010, p.1269-1274

New York, NY, USA: ACM

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14
ISOFORMS OF HMGB1 ACTIVATE NEURONAL CELLS IN VITRO AND MODULATE PAIN-LIKE BEHAVIOR IN ANIMALS
ISOFORMS OF HMGB1 ACTIVATE NEURONAL CELLS IN VITRO AND MODULATE PAIN-LIKE BEHAVIOR IN ANIMALS
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ISOFORMS OF HMGB1 ACTIVATE NEURONAL CELLS IN VITRO AND MODULATE PAIN-LIKE BEHAVIOR IN ANIMALS

Yang, H ; Zeng, Q ; Addorisio, M ; Gunasekaran, MK ; Chavan, SS ; Andersson, U ; Tracey, KJ

SHOCK, 2018, Vol.49 (6), p.28 [Periódico revisado por pares]

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15
Travel Time-Dependent Maximum Entropy Inverse Reinforcement Learning for Seabird Trajectory Prediction
Travel Time-Dependent Maximum Entropy Inverse Reinforcement Learning for Seabird Trajectory Prediction
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Travel Time-Dependent Maximum Entropy Inverse Reinforcement Learning for Seabird Trajectory Prediction

Hirakawa, Tsubasa ; Yamashita, Takayoshi ; Yoda, Ken ; Tamaki, Toru ; Fujiyoshi, Hironobu

2017 4th IAPR Asian Conference on Pattern Recognition (ACPR), 2017, p.430-435

IEEE

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16
Quantifying the Importance of Measured Metabolic Rates and Clothing Levels for Effectively Using a Predicted Mean Vote Model: A Global Sensitivity Analysis
Quantifying the Importance of Measured Metabolic Rates and Clothing Levels for Effectively Using a Predicted Mean Vote Model: A Global Sensitivity Analysis
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Quantifying the Importance of Measured Metabolic Rates and Clothing Levels for Effectively Using a Predicted Mean Vote Model: A Global Sensitivity Analysis

Thomas, Jermy ; Swenson, Tiffany ; Smith, Amanda D

ASHRAE transactions, 2019, Vol.125 (1), p.176-183 [Periódico revisado por pares]

Atlanta: American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc. (ASHRAE)

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17
MAPSSIC, a communicating MAPS-based intracerebral positrons probe for deep brain imaging in awake and freely-moving rats
MAPSSIC, a communicating MAPS-based intracerebral positrons probe for deep brain imaging in awake and freely-moving rats
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MAPSSIC, a communicating MAPS-based intracerebral positrons probe for deep brain imaging in awake and freely-moving rats

Gensolen, F. ; Ammour, L. ; Bautista, M. ; Heymes, J. ; Fieux, S. ; Kachel, M. ; Lefebvre, F. ; Pangaud, P. ; Pinot, L. ; Lanièce, P. ; Baudot, J. ; Gisquet, P. ; Zimmer, L. ; Verdier, M-A. ; Morel, C. Lyoussi, A. ; Snoj, L. ; Reynard-Carette, C. ; Vermeeren, L. ; Giot, M. ; Carette, M. ; Le Dû, P. ; Jenčič, I.

EPJ Web of Conferences, 2020, Vol.225, p.9002 [Periódico revisado por pares]

Les Ulis: EDP Sciences

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18
Animal street crossing behavior: An in-depth field study for the identification of animal street crossing behaviour using the AIMATS-methodology
Animal street crossing behavior: An in-depth field study for the identification of animal street crossing behaviour using the AIMATS-methodology
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Animal street crossing behavior: An in-depth field study for the identification of animal street crossing behaviour using the AIMATS-methodology

Erbsmehl, Christian T ; Landgraf, Tom ; Hitoshi, Yuasa

2017

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19
Remote controlled bio-stimulator and animal behavior analysis system
Remote controlled bio-stimulator and animal behavior analysis system
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Remote controlled bio-stimulator and animal behavior analysis system

Song, Weiguo ; Yuan, Kui ; Han, Taizhen ; Chai, Jie Nosach, O. Y ; Wang, Jiaqi ; Jiang, Jingshan

SPIE 2006

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20
Wireless Inertial Sensors for Monitoring Animal Behavior
Wireless Inertial Sensors for Monitoring Animal Behavior
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Wireless Inertial Sensors for Monitoring Animal Behavior

Venkatraman, S. ; Long, J.D. ; Pister, K.S.J. ; Carmena, J.M.

2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, p.378-381

IEEE

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