几篇论文实现代码:
《Self-Guided and Cross-Guided Learning for Few-shot segmentation》(CVPR 2021) GitHub:https:// github.com/zbf1991/SCL
《Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks》(CVPR 2021) GitHub:https:// github.com/3dpose/3D-Multi-Person-Pose [fig5]
《NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling》(INTERSPEECH 2021) GitHub:https:// github.com/mindslab-ai/nuwave [fig1]
《VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer》(2021) GitHub:https:// github.com/zinengtang/VidLanKD
《Semi-Supervised Raw-to-Raw Mapping》(2021) GitHub:https:// github.com/mahmoudnafifi/raw2raw [fig6]
《VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis》(2021) GitHub:https:// github.com/thuhcsi/VAENAR-TTS
《Progressively Normalized Self-Attention Network for Video Polyp Segmentation》(2021) GitHub:https:// github.com/GewelsJI/PNS-Net [fig3]
《Logic Tensor Networks》(2021) GitHub:https:// github.com/logictensornetworks/logictensornetworks [fig2]
《Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes》(2021) GitHub:https:// github.com/chenjun2hao/DDRNet.pytorch
《BAGUA: Scaling up Distributed Learning with System Relaxations》(2021) GitHub:https:// github.com/BaguaSys/bagua
《S2AND: A Benchmark and Evaluation System for Author Name Disambiguation》(2021) GitHub:https:// github.com/allenai/S2AND
《Densely Connected Time Delay Neural Network for Speaker Verification》(INTERSPEECH 2020) GitHub:https:// github.com/yuyq96/D-TDNN
《Self-Guided and Cross-Guided Learning for Few-shot segmentation》(CVPR 2021) GitHub:https:// github.com/zbf1991/SCL
《Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks》(CVPR 2021) GitHub:https:// github.com/3dpose/3D-Multi-Person-Pose [fig5]
《NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling》(INTERSPEECH 2021) GitHub:https:// github.com/mindslab-ai/nuwave [fig1]
《VidLanKD: Improving Language Understanding via Video-Distilled Knowledge Transfer》(2021) GitHub:https:// github.com/zinengtang/VidLanKD
《Semi-Supervised Raw-to-Raw Mapping》(2021) GitHub:https:// github.com/mahmoudnafifi/raw2raw [fig6]
《VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis》(2021) GitHub:https:// github.com/thuhcsi/VAENAR-TTS
《Progressively Normalized Self-Attention Network for Video Polyp Segmentation》(2021) GitHub:https:// github.com/GewelsJI/PNS-Net [fig3]
《Logic Tensor Networks》(2021) GitHub:https:// github.com/logictensornetworks/logictensornetworks [fig2]
《Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes》(2021) GitHub:https:// github.com/chenjun2hao/DDRNet.pytorch
《BAGUA: Scaling up Distributed Learning with System Relaxations》(2021) GitHub:https:// github.com/BaguaSys/bagua
《S2AND: A Benchmark and Evaluation System for Author Name Disambiguation》(2021) GitHub:https:// github.com/allenai/S2AND
《Densely Connected Time Delay Neural Network for Speaker Verification》(INTERSPEECH 2020) GitHub:https:// github.com/yuyq96/D-TDNN
近日有感 & 珊瑚的小知识~
珊瑚虫=水螅体=ポリプ=polyp,某珊瑚虫小A不断复制克隆自己,变成AAAAAAAAAAAA的聚集群体就成了一个珊瑚群体=コロニー=colony。这种珊瑚A就是群体性珊瑚。
有某珊瑚虫小F,比较独立自主,它一般就一只虫虫独立生长,这种珊瑚F就是单体性珊瑚。
比起一上来教各种不同珊瑚,可能更需要先来一篇简单的基础知识入门。
先分清楚单体/群体珊瑚,然后再讲群体可以共同构建出不同形态。然后再用珊瑚虫单体形态+群体形态来分别不同的亚纲→目→科→属。这样才对嘛……
#冲绳生物情报#
珊瑚虫=水螅体=ポリプ=polyp,某珊瑚虫小A不断复制克隆自己,变成AAAAAAAAAAAA的聚集群体就成了一个珊瑚群体=コロニー=colony。这种珊瑚A就是群体性珊瑚。
有某珊瑚虫小F,比较独立自主,它一般就一只虫虫独立生长,这种珊瑚F就是单体性珊瑚。
比起一上来教各种不同珊瑚,可能更需要先来一篇简单的基础知识入门。
先分清楚单体/群体珊瑚,然后再讲群体可以共同构建出不同形态。然后再用珊瑚虫单体形态+群体形态来分别不同的亚纲→目→科→属。这样才对嘛……
#冲绳生物情报#
接触系统由两种酶原,FXII和前激肽释放酶(PK),以及辅因子高分子量激肽原(HK)组成。血液暴露于体内激活剂(例如细胞外核酸,嗜中性粒细胞外捕获网或聚磷酸盐(PolyP)),尤其是来自病原体,但也可能是血液接触医疗设备的带负电荷的人造表面暴露时,就会触发该系统的激活。化合物与FXII结合,通过自激活过程诱导因子的构象变化,从而导致其蛋白水解切割和丝氨酸蛋白酶FXIIa的产生。蛋白酶FXIIa可以激活与HK结合的PK形成血浆激肽释放酶(PKa),后者可以相互激活FXII,从而建立正反馈放大。FXII也可以通过FXIa介导的蛋白水解作用转化为FXIIa。FXII的激活依次是FXI和FIX的激活。Gailani等人发现,凝血酶是共同途径的终末凝固蛋白酶,可以通过激活FXI为FXIa来放大自身的生成。有趣的是,PolyP可以强烈增强凝血酶介导的FXI激活。除了通过诸如FXIIa和凝血酶之类的蛋白酶激活FXI外,FXI还可以自我激活,特别是在存在PolyP或核酸的情况下。
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