Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detection Jinyuan Liu†, Xin Fan‡,∗ Zhanbo Huang‡, Guanyao Wu‡, Risheng Liu‡,§, Wei Zhong‡, Zhongxuan Lu...
The implications are either (i) failure to converge to an optimal model or (ii) vulnerability to the introduction of adversarial learning targets. Fortunately, our experiments have shown that countermeasures against security attacks are effective at thwarting attacks conducted by large coalitions of ...
a growing number of approaches have been proposed to guide the generation of drug-like compounds given the information of target proteins, stemming from creative artificial intelligence techniques such as autoregressive models11,12,13,14,15, generative adversarial networks (GAN)16, variational autoencode...
developed a new framework to robustly detect underwater seafood by integrating a generative adversarial network into a standard Faster R-CNN22. However,the method has a complex network structure and a high parametric load. In contrast, the single-stage framework avoids the use of region suggestions...
Multiple kernel learning (MKL) Enzyme: AUPR: 0:898 ± 0:010 GPCR: AUPR: 0:917 ± 0:011 Ion Channel: AUPR: 0:743 ± 0:023 Nuclear Receptor: AUPR: 0:547 ± 0:101 [43] Gold standard dataset Classification Dual Laplacian Regularized Least Squares Multiple Kernel Fusion CV1: (Enzyme: ...
Infrared small target detection plays an important role in infrared search and tracking applications. In recent years, deep learning techniques have been introduced to this task with remarkable results. However, the current method is limited by reasons such as network structure and feature extraction ...
automatic spatially-aware fashion concept discovery. In: ICCV; 2017. p. 1463–1471. Venice: IEEE/CVF (Open in a new window)Google Scholar Chen Y, Li L, Yu L, et al. UNITER: UNiversal image-TExt representation learning. In: ECCV; 2020. p. 104–120. Virtual: Springer. (Open in ...
we design a dual equivariant diffusion model for learning and generating the binding molecule geometry. Based on our previous model MDM15, we devise two equivariant kernels to simulate the local chemical bonded graph and the global distant graph. In order to ensure the relative distance between the...
Adversarial attacks can misguide the learning process by manipulating training data or leverag- ing the shared model updates to infer sensitive information about the other participants. At the same time, communi- cation-based threats can disrupt the model aggregation process or lead to security ...
Dual discriminator generative adversarial network for video anomaly detection. IEEE Access, 8:88170±88176, 2020. [21] Hyunjong Park, Jongyoun Noh, and Bumsub Ham. Learning memory-guided normality for anomaly detection. In Proceed- ings of the IEEE/CVF Conference ...