Abstract
PAGE 712 A pair of Chinese researchers propose a Selected and Refined Local Attention Module for object detection. Their framework comprises a local attention module and a feature fusion module to retain as much useful information as possible. Compared with classical object detection methods, the proposed model obtains better feature representation and discriminant power. PAGE 739 Researchers from Brazil present a new communication architecture based on the ‘Internet of Things' paradigms, the objective of the architecture is to provide a communication mechanism suitable for use in rural distribution networks, which it succeeded at. The authors also highlight the physical implementation of the network. Pipeline of proposed framework PAGE 737 Researchers from China propose a domain adversarial Siamese network which attempts to eliminate the domain influence on speech representation in Automatic Speaker Recognition applications. Results show that the network performs at least 10% better than typical methods, especially in scenarios with unknown domains and unbalanced data amounts. Time histogram with MIMO PAGE 716 Researchers representing Spain, Ecuador and Denmark have analysed the effect of correlation between forwards and backwards links on the capacity of backscatter communication systems, obtaining an analytical expression for the average capacity under a correlated Rayleigh product fading channel. Closed-form asymptotic expressions for high and low signal-to-noise ratio regimes are also obtained. Proposed network architecture PAGE 699 Professor B. Y. Kong presents a multi-touch detector architecture incorporating an efficient buffering scheme. The screen can buffer two consecutive requests simulataneously, meaning only one request is made to a buffer at a time. Implementation results show that the proposed architecture can diminish the silicon area by 36% and power consumption by 17% compared to state of the art. Average capacity as a function of average SNR at receiver for different values of the power correlation coefficient. Multi-touch detection
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.