7. A CW light from a broad-linewidth (1.2 nm) light source operating at 1551 nm is injected into a high extinction ratio (>50 dB) SOA, driven by a commercial FPGA, to modulate the light intensity with a single optical pulse or a GO-coded pulse sequence, alternatively. The ...
Intensity-modulated direct-detection Doppler LiDAR (IM-DDDL) with pseudo-random code is demonstrated for range and speed measurement of a hard target. This IM-DDDL has key features of 1) long-time coherent signal accumulation without requirement of narrow-linewidth laser source, 2) high receiving...
This finding indicates that the functional network of the cortex is neither a random network nor a scale-free network. Furthermore, we found that there are a small number of hub neurons with a very large number of functional connections. By calculating network metrics such as shortest path ...
16.【半监督学习】SimMatchV2: Semi-Supervised Learning with Graph Consistency 论文地址:arxiv.org//pdf/2308.066 开源代码:github.com/mingkai-zhen 17.【视频增强】FastLLVE: Real-Time Low-Light Video Enhancement with Intensity-Aware Lookup Table 论文地址:arxiv.org//pdf/2308.067 开源代码(即将开源...
In the 11th parameter you can indicate a series of characters to say that the transition must be blended (Z), sharp (0), or random (with various levels of intensity (1..9,A..K). Example: gradients=1,1,0,,0,0,,1,0,0,01AZ ...
Deflecting Adversarial Attacks With Pixel Deflection CVPR code 27 Mean Field Multi-Agent Reinforcement Learning ICML code 26 Visualizing and Understanding Atari Agents ICML code 26 Cascade R-CNN: Delving Into High Quality Object Detection CVPR code 25 NetGAN: Generating Graphs via Random Walks ICML cod...
To achieve this goal, we first conducted positive selection with a focusedMethanosarcina mazeiPylRS (MmPylRS) mutant library by completely randomizing residues Y306 and C348 to NNK (N = A/T/G or C, K = T or G). A hit with the Y306M and C348T mutations, exhibiting a Kla...
NetGAN: Generating Graphs via Random Walks ICML code 25 Recurrent Scene Parsing With Perspective Understanding in the Loop CVPR code 25 TOM-Net: Learning Transparent Object Matting From a Single Image CVPR code 25 Frame-Recurrent Video Super-Resolution CVPR code 24 Generative Adversarial Perturbations ...
In particular, we technically propose a novel random CNN component that can randomly convolute non-adjacent features to capture their interaction information and learn feature embeddings of key attributes to make the final recommendation. Paper Add Code RocketQA...
Exploring Context with Deep Structured models for Semantic Segmentation no code implementations • 10 Mar 2016 • Guosheng Lin, Chunhua Shen, Anton Van Den Hengel, Ian Reid We formulate deep structured models by combining CNNs and Conditional Random Fields (CRFs) for learning the patch-patch...