Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Wang, Siqi"'
Autor:
Wang, Siqi, Plummer, Bryan A.
Learning with noisy labels (LNL) is challenging as the model tends to memorize noisy labels, which can lead to overfitting. Many LNL methods detect clean samples by maximizing the similarity between samples in each category, which does not make any a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::afd3f284c9891dd06e267b1a7f747035
http://arxiv.org/abs/2306.11911
http://arxiv.org/abs/2306.11911
Open World Object Detection (OWOD) is a novel and challenging computer vision task that enables object detection with the ability to detect unknown objects. Existing methods typically estimate the object likelihood with an additional objectness branc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f1d04e60d6757057d4ee46ed9b20faf
http://arxiv.org/abs/2306.02275
http://arxiv.org/abs/2306.02275
As an emerging network model, spiking neural networks (SNNs) have aroused significant research attentions in recent years. However, the energy-efficient binary spikes do not augur well with gradient descent-based training approaches. Surrogate gradie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0a347129982b1d7c4d2655a55b5cad3
http://arxiv.org/abs/2304.13289
http://arxiv.org/abs/2304.13289
Automatic detection of multimodal fake news has gained a widespread attention recently. Many existing approaches seek to fuse unimodal features to produce multimodal news representations. However, the potential of powerful cross-modal contrastive lea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef377a4b4d75adf67539fc6bfe5c7a6e
Wireless sensor networks (WSNs) are composed of spatially distributed sensors and are considered vulnerable to attacks by worms and their variants. Due to the distinct strategies of worms propagation, the dynamic behavior varies depending on the diff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f95c90daff8c8b29b5c28d4bba56904d
http://arxiv.org/abs/2209.09984
http://arxiv.org/abs/2209.09984
We present an effective method for Intracranial Hemorrhage Detection (IHD) which exceeds the performance of the winner solution in RSNA-IHD competition (2019). Meanwhile, our model only takes quarter parameters and ten percent FLOPs compared to the w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc6859b064f5ee8647236785310d69e8
http://arxiv.org/abs/2205.07556
http://arxiv.org/abs/2205.07556
The Euclidean Steiner tree problem seeks the min-cost network to connect a collection of target locations, and it underlies many applications of wireless networks. In this paper, we present a study on solving the Euclidean Steiner tree problem using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::76bded47b8fe422cdf67b01227186b77
Layout planning is centrally important in the field of architecture and urban design. Among the various basic units carrying urban functions, residential community plays a vital part for supporting human life. Therefore, the layout planning of reside
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::397a27ea5c5c8247460bdbaa2948a1e8
Although deep neural networks (DNNs) enable great progress in video abnormal event detection (VAD), existing solutions typically suffer from two issues: (1) The localization of video events cannot be both precious and comprehensive. (2) The semantics
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff2aae5c6662e84d464ea940f227a4e1
Autor:
Wang, Siqi, Liu, Jiyuan, Yu, Guang, Liu, Xinwang, Zhou, Sihang, Zhu, En, Yang, Yuexiang, Yin, Jianping
One-class classification (OCC), which models one single positive class and distinguishes it from the negative class, has been a long-standing topic with pivotal application to realms like anomaly detection. As modern society often deals with massive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57fcc41c31e369c7129e0b9ba68188c6