Items where Subject is "46 INFORMATION AND COMPUTING SCIENCES > 4611 Machine learning > 461103 Deep learning"

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0 [feed] RSS 2.0
Group by: Creators | Item Type
Jump to: C | H | J | L | M | P | S | Y | Z
Number of items at this level: 28.

C

Calvert, Brendan, Olsen, Alex, Whinney, James, and Rahimi Azghadi, Mostafa (2021) Robotic spot spraying of Harrisia cactus (Harrisia martinii) in grazing pastures of the Australian rangelands. Plants, 10 (10). 2054.

Chaturvedi, Iti, Satapathy, Ranjan, Cavallari, Sandro, and Cambria, Erik (2019) Fuzzy commonsense reasoning for multimodal sentiment analysis. Pattern Recognition Letters, 125. pp. 264-270.

Chaturvedi, Iti, Cavallari, Sandro, Cambria, Erik, and Zheng, Vincent (2017) Learning word vectors in Deep Walk using convolution. In: Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference. pp. 323-328. From: FLAIRS-30: 30th International Florida Artificial Intelligence Research Society Conference, 22-24 May 2017, Marco Island, FL, USA.

Chaturvedi, Iti, Cambria, Erik, and Vilares, David (2016) Lyapunov filtering of objectivity for Spanish sentiment model. In: Proceedings of the International Joint Conference on Neural Networks. pp. 4474-4481. From: IJCNN: 2016 International Joint Conference on Neural Networks, 24-29 July 2016, Vancouver, Canada.

H

Hussain, Emtiaz, Hasan, Mahmudul, Rahman, Md Anisur, Lee, Ickjai, Tamanna, Tasmi, and Parvez, Mohammed Zavid (2021) CoroDet: a deep learning based classification for COVID-19 detection using chest X-ray images. Chaos Solitons and Fractals, 142. 110495.

J

Jahanbakht, Mohammad, Xiang, Wei, Robson, Barbara, and Rahimi Azghadi, Mostafa (2022) Nitrogen prediction in the Great Barrier Reef using finite element analysis with deep neural networks. Environmental Modelling & Software, 150. 105311.

Jahanbakht, Mohammad, Xiang, Wei, and Rahimi Azghadi, Mostafa (2022) Sea surface temperature forecasting with ensemble of stacked deep neural networks. IEEE Geoscience and Remote Sensing Letters, 19. 1502605.

Jahanbakht, Mohammad, Xiang, Wei, and Azghadi, Mostafa Rahimi (2022) Sediment Prediction in the Great Barrier Reef using Vision Transformer with finite element analysis. Neural Networks, 152. pp. 311-321. (In Press)

Jahanbakht, Mohammad, Xiang, Wei, Hanzo, Lajos, and Rahimi Azghadi, Mostafa (2021) Internet of underwater things and big marine data analytics — a comprehensive survey. IEEE Communications Surveys & Tutorials, 23 (2). pp. 904-956.

L

Liu, Jianan, Xiong, Weiyi, Bai, Liping, Xia, Yuxuan, Huang, Tao, Ouyang, Wanli, and Zhu, Bing (2022) Deep instance segmentation with automotive radar detection points. IEEE Transactions on Intelligent Vehicles. (In Press)

Lammie, Corey, Xiang, Wei, Linares-Barranco, Bernabé, and Rahimi Azghadi, Mostafa (2022) MemTorch: an open-source simulation framework for memristive deep learning systems. Neurocomputing, 485. pp. 124-133.

Lammie, Corey, Rahimiazghadi, Mostafa, and Ielmini, Daniele (2021) Empirical metal-oxide RRAM device endurance and retention model for deep learning simulations. Semiconductor Science and Technology, 36 (6). 065003.

Lammie, Corey, Eshraghian, Jason K., Lu, Wei D., and Rahimi Azghadi, Mostafa (2021) Memristive stochastic computing for deep learning parameter optimization. IEEE Transactions on Circuits and Systems II: Express Briefs, 68 (5). pp. 1650-1654.

Lammie, Corey, Xiang, Wei, and Rahimi Aghadi, Mostafa (2021) Towards memristive deep learning systems for real-time mobile epileptic seizure prediction. In: Proceedings of the IEEE International Symposium on Circuits and Systems. From: ISCAS 2021: IEEE International Symposium on Circuits and Systems, 22-28 May 2021, Daegu, Korea.

Laradji, Issam H., Saleh, Alzayat, Rodriguez, Pau, Nowrouzezahrai, Derek, Rahimi Azghadi, Mostafa, and Vazquez, David (2021) Weakly supervised underwater fish segmentation using affinity LCFCN. Scientific Reports, 11. p. 17379.

Liu, Hong-Bin (2020) Predictive spatio-temporal modelling with neural networks. PhD thesis, James Cook University.

Liu, Hong-Bin, and Lee, Ickjai (2020) Towards realistic meteorological predictive learning using conditional GAN. IEEE Access, 8. pp. 93179-93186.

Liu, Hong-Bin, Wu, Hao, Sun, Weiwei, and Lee, Ickjai (2019) Spatio-temporal GRU for trajectory classification. In: Proceedings of the 19th IEEE International Conference on Data Mining. pp. 1228-1233. From: ICDM 2019: 19th IEEE International Conference on Data Mining, 8-11 November 2019, Beijng, China.

Liu, Hongbin, and Lee, Ickjai (2017) End-to-end trajectory transportation mode classification using Bi-LSTM recurrent neural network. In: Proceedings of the 12th International Conference on Intelligent Systems and Knowledge Engineering. 158. From: ISKE 2017: 12th International Conference on Intelligent Systems and Knowledge Engineering, 24-26 November 2017, Nanjing, China.

M

Madhukumar, Neethu, Wang, Eric, Zhang, Yi-Fan, and Xiang, Wei (2021) Consensus forecast of rainfall using hybrid climate learning model. IEEE Internet of Things Journal, 8 (9). pp. 7270-7278.

P

Possemiers, Aidan, and Lee, Ickjai (2021) Evaluating deep learned voice compression for use in video games. Expert Systems with Applications, 181. 115180.

Poria, Soujanya, Chaturvedi, Iti, Cambria, Erik, and Hussian, Amir (2017) Convolutional MKL based multimodal emotion recognition and sentiment analysis. In: Proceedings of the 16th International Conference on Data Mining. pp. 439-448. From: ICDM 2016: 16th International Conference on Data Mining, 12-15 December 2016, Barcelona, Spain.

S

Saleh, Alzayat, Sheaves, Marcus, and Rahimi Azghadi, Mostafa (2022) Computer vision and deep learning for fish classification in underwater habitats: A survey. Fish and Fisheries. (In Press)

Schoenhoff, Kurt, Holdsworth, Jason, and Lee, Ickjai (2020) Efficient semantic segmentation through dense upscaling convolutions. In: Proceedings of the 3rd International Conference on Software Engineering and Information Management. pp. 244-248. From: ICSIM'20: 3rd International Conference on Software Engineering and Information Management, 12-15 January 2020, Sydney, NSW, Australia.

Y

Young, Tom, Cambria, Erik, Chaturvedi, Iti, Zhou, Hao, Biswas, Subham, and Huang, Minlie (2018) Augmenting end-to-end dialogue systems with commonsense knowledge. In: Proceedings of the 32nd AAAI Conference on Artificial Intelligence. pp. 4970-4977. From: AAAI-18: 32nd AAAI Conference on Artificial Intelligence, 2-7 February 2018, New Orleans, LA, USA.

Yan, Ke, Wang, Xudong, Du, Yang, Jin, Ning, Huang, Haichao, and Zhou, Hangxia (2018) Multi-step short-term power consumption forecasting with a hybrid deep learning strategy. Energies, 11. 3089.

Z

Zeng, Yongkang, Chen, Jingjing, Jin, Ning, Jin, Xiaoping, and Du, Yang (2022) Air quality forecasting with hybrid LSTM and extended stationary wavelet transform. Building and Environment, 213. 108822.

Zhou, Hangxia, Liu, Qian, Yan, Ke, and Du, Yang (2021) Deep learning enhanced solar energy forecasting with AI-driven IoT. Wireless Communications and Mobile Computing, 2021. 9249387.

This list was generated on Thu Aug 18 22:59:06 2022 AEST.