Different generalized convolution operations have been introduced to counteract this. We go beyond these by leveraging guidance data to redefine their inherent notion of proximity. Our proposed network layer builds on the permutohedral lattice, which performs sparse convolutions in a high-dimensional ...
M. (2016). Sparse representation-based open set recognition. In TPAMI. Zhang, J., Fu, Q., Chen, X., Du, L., Li, Z., Wang, G., Han, S., & Zhang, D. (2023a). Out-of-distribution detection based on in-distribution data patterns memorization with modern Hopfield energy. In ...
We present new generalized convolutions with weight-function associated with the Fourier and Hartley transforms, and consider applications. Namely, using the generalized convolutions, we construct normed rings on the space L 1 ( d ), provide the sufficient and necessary condition for the solvability...
In each visualization we see only strong, sparse activation contributing to the models decision due to the GMP layer at the top of the network. Example: true positive Arguably the strongest activation overall appears to happen when almost every channel simultaneously increases, which can happen ...
This work proposes a tool condition monitoring system based on a generalized multi-stage deep machine learning framework for real-time measurement of flank wear in milling processes. At low computational cost, a deep wavelet scattering convolution neural network framework was developed and optimized to...
Furthermore, GENFIRE can be easily adapted to incorporate mathematical regularization to reconstruct 3D sparse objects from a small number of projections. Looking forward, we expect GENFIRE can be applied to a plethora of imaging modalities to address a wide range of scientific problems. Software ...
中心思想 探究为什么one-stage detection(dense approach)会比two-stage(sparse approach)性能低。查出:根本原因是分类分支中前景&背景的比例严重失衡 为了解决这个问题,从Loss入手提出了focal loss,用于调整Loss低(分得比较好的)样本的权重,从而防止Loss高的少量样本被大量Loss低的样本淹没 为了验证focal lo...Activity...
[4] Second, in addition to the analytical error always associated with reported concentrations, spatial and temporal variability in end-member concentrations is ubiquitous at the scales considered, and is nigh impossible to characterize adequately using inevitably sparse sampling [Beven, 1989; Burns et...
bands at 10 m spatial resolution and resampled the 20 m bands to 10 m using a cubic convolution kernel. To improve the geometric consistency of Sentinel-2 time series, individual images were co-registered using theLandsatSentinel Registration (LSReg) algorithm which matches Sentinel-2 images to ...
Abstract Leptin has been shown to modulate intestinal inflammation in mice. However, clinical evidence regarding its immune-stimulatory potential in human Crohn’s disease remains sparse. We here describe a patient with the unique combination of acquired generalized lipodystrophy and Crohn’s disease (AG...