Image retrieval with deep learning by Tan, Joe Chin Yong

“…The query images are distorted with the 3 methods mentioned with different values of sigma, variance and quality. …”
Get full text

Efficient rare event sampling with unsupervised normalizing flows by Asghar, Solomon, Pei, Qing-Xiang, Volpe, Giorgio, Ni, Ran

“…Classical computational methods to sample rare events remain prohibitively inefficient and are bottlenecks for enhanced samplers that require prior data. …”
Get full text

Fish classification and deep learning by Zhang, Dawei

Get full text

Transfer learning on UR robots by Yu, Xiwei

“…As neural networks and deep learning develop, researchers are continually exploring the capabilities and potential of using data-driven methods to control robots. …”
Get full text

Descriptor learning for efficient retrieval by Philbin, J, Isard, M, Sivic, J, Zisserman, A

“…Scalable, stochastic gradient methods are used for the optimization.</p> <br> <p>For the case of particular object retrieval, we demonstrate impressive gains in performance on a ground truth dataset: our learnt 32-D descriptor without spatial re-ranking outperforms a baseline method using 128-D SIFT descriptors with spatial re-ranking.…”

Online learning for search and classification by Nguyen, Thanh Tam

“…(i) Feature selection: we have investigated a number of newly supervised term weighting methods to improve the performance of text classification; (ii) Online classification: we have proposed several online learning algorithms that can be used for topic classification; (iii) Two-view online learning: we have proposed a two-view online learning algorithm, which can work on two-view datasets; (iv) Online learning-to-rank: for search engine, we have proposed an online learning-to-rank algorithm, which was to learn a scoring function to re-rank the search result.…”
Get full text

Optimization strategies for federated learning by Zhang, Tinghao

“…We achieve this through a deep reinforcement learning-based scheduling strategy and an optimized bandwidth allocation method, enabling FL to achieve target accuracy with reduced system costs. …”
Get full text

Reinforcement learning for robot assembly by Vuong Quoc Nghia

“…Finally, this thesis examines methods to narrow the reality gap - the fundamental problem in sim-to-real reinforcement learning. …”
Get full text

Vision language representation learning by Yang, Xiaofeng

“…Despite its significance, learning effective vision language representation remains challenging due to several reasons. …”
Get full text

Unsupervised generative variational continual learning by Liu, Guimeng

“…Recent research in continual learning generally incorporates two of these methods to obtain better performance. …”
Get full text

iTD3-CLN: learn to navigate in dynamic scene through Deep Reinforcement Learning by Jiang, Haoge, Esfahani, Mahdi Abolfazli, Wu, Keyu, Wan, Kong-wah, Heng, Kuan-kian, Wang, Han, Jiang, Xudong

“…In contrast to the conventional methods such as the DWA, our approach is found superior in the following ways: no need for prior knowledge of the environment and metric map, lower reliance on an accurate sensor, learning emergent behavior in dynamic scene that is intuitive, and more remarkably, able to transfer to the real robot without further fine-tuning. …”
Get full text

MAS.714J / STS.445J Technologies for Creative Learning, Fall 2004 by Resnick, Mitchel

Subjects: “…learning…”
Get full text

Refining learning models in grammatical inference by Wang, Xiangrui

“…We introduce the use of recurrent neural networks (RNNs) and present a pruning learning method to avoid the exponential space costs. …”
Get full text

16.901 Computational Methods in Aerospace Engineering, Spring 2003 by Darmofal, David L.

Get full text

15.053 Optimization Methods in Management Science, Spring 2007 by Mamani, Hamed, Orlin, James, Metzger, Michael, Narayanaswamy, Murali

Get full text

16.901 Computational Methods in Aerospace Engineering, Spring 2005 by Darmofal, David

Get full text

Explore anomaly detection and localization methods for medical imaging data by Yu, Tianze

“…Motivated by this, we introduce Contrastive Learning guided GAN (CLGAN), which leverages unlabeled mixed data and contrastive learning to guide the generation process. …”
Get full text

Handbook of Research on Deep Learning Techniques for Cloud-Based Industrial IoT / by Swarnalatha, P. (Purushotham), 1977-, editor 656271, Prabu, S., 1981-, editor 656272, IGI Global (Online service) 631983

“…"Deep Learning Techniques for Cloud-Based Industrial IoT aims to demonstrate how computer scientists and engineers of today might employ artificial intelligence in practical applications with the emerging cloud and IoT technologies. …”
Get full text

Data-driven methods to predict the stability metrics of catalytic nanoparticles by Prabhu, Asmee M., Choksi, Tej S.

“…In this review we discuss the recent advances in data-driven methods to predict stability metrics of nanoparticles.…”
Get full text

Incremental learning technologies for semantic segmentation by Yang, Yizhuo

“…In addition, other incremental learning technologies - knowledge distillation, replay and parameter freezing are also applied to the proposed method to further assist the model in overcoming catastrophic forgetting. …”
Get full text